Blue Machines AI

14 jobs at Blue Machines AI

ML Research Engineer, Speech

Bengaluru, Karnataka, IN · Onsite · 1 week ago

About Blue Machines and the Speech Research Team Blue Machines (ApnaTime Tech Pvt. Ltd.) builds enterprise voice AI agents for banks, insurers, healthcare and telecom companies. Our platform has handled tens of millions of production voice minutes, is ISO 27001/27701 and SOC 2 Type II certified, and runs both on cloud and on-prem. We already run our own models in production: Aurora (STT tuned for BFSI), Floe (language-switch detection), end-of-utterance models, and noise cancellation, all on BM Zap, our low-latency voice framework. The Speech Research team takes this further: better accuracy on Indian languages and code-mixed speech, natural expressive TTS, and full-duplex speech-to-speech models that cut latency across the whole conversation. What makes this work different Real traffic: your model ships to live enterprise calls, not a leaderboard Hard problems: 8 kHz telephony audio, Hinglish and code-switching, accents, noisy environments, domain entities (loan numbers, policy IDs, names) Tight latency budgets: streaming inference where every 50 ms is noticed by callers A full loop: data, training, evaluation, serving and production feedback in one team Location: Bengaluru (on-site / hybrid) · Team: Speech Research, reporting into the CTO org Role 1: ML Research Engineer, Speech (1–3 years) You will build speech models from the ground up: implement architectures from scratch, pre-train them on large audio corpora, then adapt and ship them. You'll own well-scoped experiments from data to deployed checkpoint, with guidance from senior researchers. What you will do Pre-train STT models from scratch (Conformer/Zipformer encoders, CTC/RNN-T/TDT decoders, self-supervised pre-training like wav2vec 2.0/HuBERT/BEST-RQ), then fine-tune them for Indian languages, Hinglish and BFSI vocabulary Train TTS models from scratch (flow-matching, diffusion, neural codec LMs, vocoders) and extend them to new voices, languages and speaking styles Build speech-to-speech components from scratch: audio tokenizers and codecs, speech encoders connected to LLMs, streaming decoders Turn papers and new ideas into working PyTorch code: write the model, tokenizer and training loop yourself, and train from random initialisation Build data pipelines: cleaning, segmentation, forced alignment, pseudo-labelling, augmentation (noise, codecs, 8 kHz telephony simulation) Maintain evaluation suites: WER/CER, entity error rate, code-switch accuracy, MOS and speaker similarity, latency (time to first token / byte) Optimise models for serving: quantisation, streaming chunking, ONNX/TensorRT export, batching on GPUs Analyse production errors, turn them into test sets, and close the loop with the platform team Write clear experiment reports and share findings in weekly research reviews What you bring 1–3 years in ML, with at least one real project in speech or audio (industry, research lab, or a strong thesis) B.Tech/M.Tech/MS in CS, EE or a related field; a PhD is not required Strong Python and PyTorch; able to implement a model architecture and training loop from scratch, not just call APIs or fine-tune checkpoints Working knowledge of speech basics: spectrograms, MFCC/mel features, CTC, attention-based seq2seq, vocoders Hands-on with at least one of: NeMo, ESPnet, Hugging Face Transformers/Audio, fairseq, Coqui, k2/icefall Has trained at least one model from random initialisation (speech, audio or language), including multi-GPU jobs, mixed precision and experiment tracking (W&B, MLflow) Careful with evaluation: you know why a WER number can mislead, and you check your data Nice to have Speak or understand Hindi or another Indian language Publications, Kaggle/benchmark results, or open-source contributions in speech Exposure to real-time audio (WebRTC, SIP, streaming inference) or telephony audio Familiarity with LLM fine-tuning (LoRA, SFT) or audio-language models What success looks like in 6 months Contributed to a pre-trained-from-scratch model that shipped to production with a measured gain on a customer-relevant test set Owns a piece of the evaluation or data pipeline that others rely on Runs experiments independently and reports results the team can trust

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Senior ML Research Scientist, Speech

Bengaluru, Karnataka, IN · Onsite · 1 week ago

About Blue Machines and the Speech Research team Blue Machines (ApnaTime Tech Pvt. Ltd.) builds enterprise voice AI agents for banks, insurers, healthcare and telecom companies. Our platform has handled tens of millions of production voice minutes, is ISO 27001/27701 and SOC 2 Type II certified, and runs both on cloud and on-prem. We already run our own models in production: Aurora (STT tuned for BFSI), Floe (language-switch detection), end-of-utterance models, and noise cancellation, all on BM Zap, our low-latency voice framework. The Speech Research team takes this further: better accuracy on Indian languages and code-mixed speech, natural expressive TTS, and full-duplex speech-to-speech models that cut latency across the whole conversation. What makes this work different Real traffic: your model ships to live enterprise calls, not a leaderboard Hard problems: 8 kHz telephony audio, Hinglish and code-switching, accents, noisy environments, domain entities (loan numbers, policy IDs, names) Tight latency budgets: streaming inference where every 50 ms is noticed by callers A full loop: data, training, evaluation, serving and production feedback in one team Location: Bengaluru (on-site / hybrid) · Team: Speech Research, reporting into the CTO org Senior ML Research Scientist, Speech (3–6 years) You will own a research direction (STT, TTS or speech-to-speech) end to end. That means designing new architectures, pre-training foundation models from scratch on large multilingual audio, and getting them into production, while mentoring engineers on the team. What you will do Lead one research track and set its roadmap with the CTO and product leads, tied to customer metrics (accuracy, naturalness, latency, cost per minute) Design novel architectures and pre-train speech foundation models from scratch on large multilingual corpora (100k+ hours), including self-supervised pre-training, tokenizer and codec design, and scaling experiments. Fine-tuning and continued training are tools, not the whole job STT: streaming ASR with low time-to-first-token, code-switch robustness, contextual biasing for names and entities, domain adaptation for BFSI and healthcare TTS: expressive, low-latency streaming TTS for Indian languages; voice cloning, prosody and emotion control, pronunciation of numbers, dates and mixed-script text Speech-to-speech: Full-duplex conversational models built in-house: our own audio tokenizers and codecs, speech-LLM pre-training and alignment, interruption and turn-taking, end-of-utterance prediction Build the data strategy: sourcing, licensing, synthetic data generation, labelling quality and consent-compliant use of production audio Define evaluation standards and benchmarks that predict real call outcomes, and run honest comparisons against external vendors Make serving trade-offs with the platform team: distillation, quantisation, GPU concurrency per model, on-prem footprints Mentor 1–3 engineers; review experiment designs and code Publish or open-source selectively where it strengthens our position What you bring 3–6 years in ML, with at least 2–3 years focused on speech (ASR, TTS, speaker/voice or audio-language models) MS or PhD in CS, EE or related field, or equivalent depth shown through shipped work Track record of pre-training at least one speech or audio model from scratch (not only fine-tuning) that reached production or strong published results Deep knowledge of modern architectures: Conformer/Zipformer, RNN-T/TDT, encoder–decoder ASR, flow-matching and diffusion TTS, neural codecs (EnCodec, DAC, Mimi), speech-LLMs Large-scale pre-training experience: distributed training (FSDP/DeepSpeed/Megatron) on multi-node GPU clusters, 100k+ audio hours, scaling laws and compute budgeting, data loading at scale, debugging loss spikes and unstable runs Strong experimental design: ablations, significance, avoiding test-set leakage Clear written and spoken communication with engineers, product and customers Nice to have Publications at Interspeech, ICASSP, ACL/EMNLP, NeurIPS or similar Experience with Indic languages, low-resource languages or code-switching Built streaming or real-time speech systems with strict latency SLAs Experience with RL or preference tuning for speech (e.g. naturalness rewards) or LLM post-training Contributions to open-source speech toolkits What success looks like in 12 months Your track has shipped a model pre-trained from scratch by Blue Machines that beats the vendor it replaces on our benchmark and reduces cost or latency A clear, reproducible training and evaluation stack for your area Engineers you mentor are running experiments independently

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Lead Forward Deployment Engineer- Government Division

Bengaluru, Karnataka, IN · Onsite · 1 week ago

About Blue Machines Blue Machines is an enterprise Voice AI platform that lets organisations talk to millions of people in their own language. Our Government Division runs production voice AI for state departments. Our GCAS AI Assistant in Gujarat serves 3.75 lakh applicants across 2,461 colleges at 99.96% accuracy. We're scaling across departments and states, and we need a senior engineer to build and lead the team that makes every deployment land. The role You'll be the technical owner of our government deployments and the leader of our Forward Deployed Engineering team. You'll get your hands dirty on the hardest deployments, and be the person senior officials trust on anything technical. You'll partner closely with the Division head on proposals, pricing inputs and delivery commitments. What you'll do Own delivery Act as technical accountable owner for every government deployment, from scoping through UAT, go-live and post-launch reporting. Personally lead the most complex or high-stakes deployments and integrations. Present architecture, performance and roadmap to senior officials, including IAS-level stakeholders and department heads. Own data security, hosting and compliance conversations: SDC/NIC, MeitY-empanelled cloud and data residency. Lead technical solutioning for RFPs and proposals: solution architecture, effort estimates, SLAs and technical compliance responses. Run technical demos and pre-bid discussions with departments. Turn field learnings into platform priorities with product and engineering. You're the voice of the government customer internally. Requirements Must-haves ~10 years in software engineering, with 4+ years in client-facing deployment, solutions or implementation engineering. 2+ years leading engineers, formally or as a tech lead across multiple concurrent deployments. Deep hands-on skills: Python and/or TypeScript, APIs and integrations, SQL, cloud infrastructure (AWS/GCP), and production monitoring. Practical experience shipping LLM-based systems: prompting, RAG, function calling, evaluation and guardrails. A proven record of delivering complex systems to enterprise or public-sector clients under tight timelines and shifting requirements. Executive-level communication in English and Hindi, including writing and presenting for non-technical senior audiences. Willingness to travel and to be on-site during critical deployment phases. Good to have: Direct experience delivering for central or state government, PSUs, or large government-funded programmes. Working knowledge of government procurement and delivery: RFPs and technical bids, work orders, UAT and sign-off, payment milestones, and audit expectations. Gujarati proficiency, or another regional language for future state deployments. Preferred: Voice or telephony depth: SIP, IVR, contact-centre platforms, ASR/TTS vendors. Background at a system integrator, GovTech firm or high-growth startup. Benefits Your deployments reach lakhs of citizens, and you'll have direct visibility with senior government leadership. You'll get meaningful ownership over how Indian-language voice AI gets delivered to the public sector.

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Forward Deployed Engineer (Voice AI / Telephony) - Bengaluru

Bengaluru, Karnataka, IN · Onsite · 2 weeks ago

Job Title: Forward Deployed Engineer Experience: 3-5 Years About the Company: Blue Machines builds production Voice AI for India's largest enterprises—handling millions of live conversations in Hindi, Hinglish, and regional languages. As a Forward Deployed Engineer, you will design, build, integrate, support, and debug production-grade AI agents end-to-end. You are directly responsible for the delivery and execution of your agent, not a partner handing off to it. You will bridge the gap between client systems and the Blue Machines platform across APIs, cloud services, and AI frameworks. The Role We are seeking a Forward Deployed Engineer (FDE) who bridges the gap between deep software engineering, cutting edge AI agent orchestration, and client delivery. In this role, you aren't just writing specifications or handing off prototypes you directly design, build, deploy, optimize, and debug production AI agents end-to-end. You will embed deeply with client environments to build seamless integrations while taking full technical ownership of agent performance in the wild. What You'll Do ● End-to-End AI Agent Architecture: Design, prompt, build, and deploy production voice agents, including guardrails, conversation design, and tool-calling logic. ● Production Integration Engineering: Build scalable backend integrations (REST APIs, WebSockets, webhooks, callbacks, CRM writes) connecting the Blue Machines platform with enterprise systems. ● AI Orchestration & Ecosystems: Implement AI/LLM frameworks using LangChain, OpenAI APIs, or similar SDKs to deliver intelligent workflows. ● System Observability & Root-Cause Analysis: Read system logs, traces, and call flows to run rigorous root-cause analysis—proving whether an issue stems from prompt design, platform layer, or data pipelines. ● Agent Evaluation & Funnel Optimization: Continuously monitor and optimize agent metrics (completion rate, hallucination rate, latency, cost) and run funnel experiments on conversation cadence. ● Client Technical Leadership: Partner directly with client engineering teams, lead technical workshops, manage expectations with clarity, and travel for live-call reviews. What We Look For ● Core Experience: (3-5) years of software development experience, with at least 2+ years of hands-on experience shipping live LLM/AI applications (agents, RAG, or chatbots; voice experience is a plus). ● Core Backend Skills: Proficiency in Python or Java for backend architecture and integration work. ● Cloud & Web Architecture: Hands-on experience with cloud platforms (preferably GCP) along with deep knowledge of APIs, WebSockets, and auth protocols (OAuth2, JWT). ● Data Fluency: Comfortable pulling and analyzing data independently using SQL, Python, or Sheets. ● Communication & Presence: Strong client-facing communication skills with the ability to explain technical complexities in plain terms. ● Mobility: Willingness to travel for on-site client workshops and deployment reviews. Nice to Have ● Knowledge of telephony stacks and real-time protocols (SIP, WebRTC, Twilio, Avaya, Ubona). ● Experience with Voice AI or Conversational AI Systems

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Forward Deployed Engineer (Voice AI / Telephony) - Ahmedabad

Ahmedabad, Gujarat, IN · Onsite · 3 weeks ago

Job Title: Forward Deployed Engineer Experience: 3-5 Years About the Company: Blue Machines builds production Voice AI for India's largest enterprises—handling millions of live conversations in Hindi, Hinglish, and regional languages. As a Forward Deployed Engineer, you will design, build, integrate, support, and debug production-grade AI agents end-to-end. You are directly responsible for the delivery and execution of your agent, not a partner handing off to it. You will bridge the gap between client systems and the Blue Machines platform across APIs, cloud services, and AI frameworks. The Role We are seeking a Forward Deployed Engineer (FDE) who bridges the gap between deep software engineering, cutting edge AI agent orchestration, and client delivery. In this role, you aren't just writing specifications or handing off prototypes you directly design, build, deploy, optimize, and debug production AI agents end-to-end. You will embed deeply with client environments to build seamless integrations while taking full technical ownership of agent performance in the wild. What You'll Do ● End-to-End AI Agent Architecture: Design, prompt, build, and deploy production voice agents, including guardrails, conversation design, and tool-calling logic. ● Production Integration Engineering: Build scalable backend integrations (REST APIs, WebSockets, webhooks, callbacks, CRM writes) connecting the Blue Machines platform with enterprise systems. ● AI Orchestration & Ecosystems: Implement AI/LLM frameworks using LangChain, OpenAI APIs, or similar SDKs to deliver intelligent workflows. ● System Observability & Root-Cause Analysis: Read system logs, traces, and call flows to run rigorous root-cause analysis—proving whether an issue stems from prompt design, platform layer, or data pipelines. ● Agent Evaluation & Funnel Optimization: Continuously monitor and optimize agent metrics (completion rate, hallucination rate, latency, cost) and run funnel experiments on conversation cadence. ● Client Technical Leadership: Partner directly with client engineering teams, lead technical workshops, manage expectations with clarity, and travel for live-call reviews. What We Look For ● Core Experience: (3-5) years of software development experience, with at least 2+ years of hands-on experience shipping live LLM/AI applications (agents, RAG, or chatbots; voice experience is a plus). ● Core Backend Skills: Proficiency in Python or Java for backend architecture and integration work. ● Cloud & Web Architecture: Hands-on experience with cloud platforms (preferably GCP) along with deep knowledge of APIs, WebSockets, and auth protocols (OAuth2, JWT). ● Data Fluency: Comfortable pulling and analyzing data independently using SQL, Python, or Sheets. ● Communication & Presence: Strong client-facing communication skills with the ability to explain technical complexities in plain terms. ● Mobility: Willingness to travel for on-site client workshops and deployment reviews. Nice to Have ● Knowledge of telephony stacks and real-time protocols (SIP, WebRTC, Twilio, Avaya, Ubona). ● Experience with Voice AI or Conversational AI Systems

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Forward Deployed Engineer (Voice AI / Telephony) - Delhi

Delhi, Delhi, IN · Onsite · 3 weeks ago

Job Title: Forward Deployed Engineer Experience: 3-5 Years About the Company: Blue Machines builds production Voice AI for India's largest enterprises—handling millions of live conversations in Hindi, Hinglish, and regional languages. As a Forward Deployed Engineer, you will design, build, integrate, support, and debug production-grade AI agents end-to-end. You are directly responsible for the delivery and execution of your agent, not a partner handing off to it. You will bridge the gap between client systems and the Blue Machines platform across APIs, cloud services, and AI frameworks. The Role We are seeking a Forward Deployed Engineer (FDE) who bridges the gap between deep software engineering, cutting edge AI agent orchestration, and client delivery. In this role, you aren't just writing specifications or handing off prototypes you directly design, build, deploy, optimize, and debug production AI agents end-to-end. You will embed deeply with client environments to build seamless integrations while taking full technical ownership of agent performance in the wild. What You'll Do ● End-to-End AI Agent Architecture: Design, prompt, build, and deploy production voice agents, including guardrails, conversation design, and tool-calling logic. ● Production Integration Engineering: Build scalable backend integrations (REST APIs, WebSockets, webhooks, callbacks, CRM writes) connecting the Blue Machines platform with enterprise systems. ● AI Orchestration & Ecosystems: Implement AI/LLM frameworks using LangChain, OpenAI APIs, or similar SDKs to deliver intelligent workflows. ● System Observability & Root-Cause Analysis: Read system logs, traces, and call flows to run rigorous root-cause analysis—proving whether an issue stems from prompt design, platform layer, or data pipelines. ● Agent Evaluation & Funnel Optimization: Continuously monitor and optimize agent metrics (completion rate, hallucination rate, latency, cost) and run funnel experiments on conversation cadence. ● Client Technical Leadership: Partner directly with client engineering teams, lead technical workshops, manage expectations with clarity, and travel for live-call reviews. What We Look For ● Core Experience: (3-5) years of software development experience, with at least 2+ years of hands-on experience shipping live LLM/AI applications (agents, RAG, or chatbots; voice experience is a plus). ● Core Backend Skills: Proficiency in Python or Java for backend architecture and integration work. ● Cloud & Web Architecture: Hands-on experience with cloud platforms (preferably GCP) along with deep knowledge of APIs, WebSockets, and auth protocols (OAuth2, JWT). ● Data Fluency: Comfortable pulling and analyzing data independently using SQL, Python, or Sheets. ● Communication & Presence: Strong client-facing communication skills with the ability to explain technical complexities in plain terms. ● Mobility: Willingness to travel for on-site client workshops and deployment reviews. Nice to Have ● Knowledge of telephony stacks and real-time protocols (SIP, WebRTC, Twilio, Avaya, Ubona). ● Experience with Voice AI or Conversational AI Systems

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Forward Deployed Engineer (Voice AI / Telephony) - Mumbai

Mumbai, Maharashtra, IN · Onsite · 3 weeks ago

Job Title: Forward Deployed Engineer Experience: 3-5 Years About the Company: Blue Machines builds production Voice AI for India's largest enterprises—handling millions of live conversations in Hindi, Hinglish, and regional languages. As a Forward Deployed Engineer, you will design, build, integrate, support, and debug production-grade AI agents end-to-end. You are directly responsible for the delivery and execution of your agent, not a partner handing off to it. You will bridge the gap between client systems and the Blue Machines platform across APIs, cloud services, and AI frameworks. The Role We are seeking a Forward Deployed Engineer (FDE) who bridges the gap between deep software engineering, cutting edge AI agent orchestration, and client delivery. In this role, you aren't just writing specifications or handing off prototypes you directly design, build, deploy, optimize, and debug production AI agents end-to-end. You will embed deeply with client environments to build seamless integrations while taking full technical ownership of agent performance in the wild. What You'll Do ● End-to-End AI Agent Architecture: Design, prompt, build, and deploy production voice agents, including guardrails, conversation design, and tool-calling logic. ● Production Integration Engineering: Build scalable backend integrations (REST APIs, WebSockets, webhooks, callbacks, CRM writes) connecting the Blue Machines platform with enterprise systems. ● AI Orchestration & Ecosystems: Implement AI/LLM frameworks using LangChain, OpenAI APIs, or similar SDKs to deliver intelligent workflows. ● System Observability & Root-Cause Analysis: Read system logs, traces, and call flows to run rigorous root-cause analysis—proving whether an issue stems from prompt design, platform layer, or data pipelines. ● Agent Evaluation & Funnel Optimization: Continuously monitor and optimize agent metrics (completion rate, hallucination rate, latency, cost) and run funnel experiments on conversation cadence. ● Client Technical Leadership: Partner directly with client engineering teams, lead technical workshops, manage expectations with clarity, and travel for live-call reviews. What We Look For ● Core Experience: (3-5) years of software development experience, with at least 2+ years of hands-on experience shipping live LLM/AI applications (agents, RAG, or chatbots; voice experience is a plus). ● Core Backend Skills: Proficiency in Python or Java for backend architecture and integration work. ● Cloud & Web Architecture: Hands-on experience with cloud platforms (preferably GCP) along with deep knowledge of APIs, WebSockets, and auth protocols (OAuth2, JWT). ● Data Fluency: Comfortable pulling and analyzing data independently using SQL, Python, or Sheets. ● Communication & Presence: Strong client-facing communication skills with the ability to explain technical complexities in plain terms. ● Mobility: Willingness to travel for on-site client workshops and deployment reviews. Nice to Have ● Knowledge of telephony stacks and real-time protocols (SIP, WebRTC, Twilio, Avaya, Ubona). ● Experience with Voice AI or Conversational AI Systems

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Forward Deployed Engineer (Voice AI / Telephony) - Chennai

Chennai, Tamil Nadu, IN · Onsite · 3 weeks ago

Job Title: Forward Deployed Engineer Experience: 3-6 Years About the Company: Blue Machines builds production Voice AI for India's largest enterprises—handling millions of live conversations in Hindi, Hinglish, and regional languages. As a Forward Deployed Engineer, you will design, build, integrate, support, and debug production-grade AI agents end-to-end. You are directly responsible for the delivery and execution of your agent, not a partner handing off to it. You will bridge the gap between client systems and the Blue Machines platform across APIs, cloud services, and AI frameworks. The Role We are seeking a Forward Deployed Engineer (FDE) who bridges the gap between deep software engineering, cutting edge AI agent orchestration, and client delivery. In this role, you aren't just writing specifications or handing off prototypes you directly design, build, deploy, optimize, and debug production AI agents end-to-end. You will embed deeply with client environments to build seamless integrations while taking full technical ownership of agent performance in the wild. What You'll Do ● End-to-End AI Agent Architecture: Design, prompt, build, and deploy production voice agents, including guardrails, conversation design, and tool-calling logic. ● Production Integration Engineering: Build scalable backend integrations (REST APIs, WebSockets, webhooks, callbacks, CRM writes) connecting the Blue Machines platform with enterprise systems. ● AI Orchestration & Ecosystems: Implement AI/LLM frameworks using LangChain, OpenAI APIs, or similar SDKs to deliver intelligent workflows. ● System Observability & Root-Cause Analysis: Read system logs, traces, and call flows to run rigorous root-cause analysis—proving whether an issue stems from prompt design, platform layer, or data pipelines. ● Agent Evaluation & Funnel Optimization: Continuously monitor and optimize agent metrics (completion rate, hallucination rate, latency, cost) and run funnel experiments on conversation cadence. ● Client Technical Leadership: Partner directly with client engineering teams, lead technical workshops, manage expectations with clarity, and travel for live-call reviews. What We Look For ● Core Experience: (3-6) years of software development experience, with at least 2+ years of hands-on experience shipping live LLM/AI applications (agents, RAG, or chatbots; voice experience is a plus). ● Core Backend Skills: Proficiency in Python or Java for backend architecture and integration work. ● Cloud & Web Architecture: Hands-on experience with cloud platforms (preferably GCP) along with deep knowledge of APIs, WebSockets, and auth protocols (OAuth2, JWT). ● Data Fluency: Comfortable pulling and analyzing data independently using SQL, Python, or Sheets. ● Communication & Presence: Strong client-facing communication skills with the ability to explain technical complexities in plain terms. ● Mobility: Willingness to travel for on-site client workshops and deployment reviews. Nice to Have ● Knowledge of telephony stacks and real-time protocols (SIP, WebRTC, Twilio, Avaya, Ubona). ● Experience with Voice AI or Conversational AI Systems

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Evaluation & Insights Intern, AI Delivery

Bengaluru, Karnataka, IN · Onsite · 3 weeks ago

Evaluation & Insights Intern, AI Delivery : Blue Machines · Bengaluru (WFO)· 3–6 Months · B2B/Enterprise AI/SaaS The Inflection Point Voice AI is past the "interesting demo" stage. Enterprises aren't asking whether AI can handle their customer interactions anymore — they're asking why some conversations succeed while others fail. Understanding that difference is one of the most important challenges in enterprise Voice AI today. Blue Machines runs production systems handling millions of conversations for India's largest airlines, banks, mutual funds, and retail chains. Not prototypes. Live. At scale. We are looking for QA Interns who are naturally curious about understanding what happens inside those conversations, identifying why issues occur, and helping teams continuously improve the customer experience. The Role This is a hands-on, analytical role at the intersection of Quality Assurance, Operations, Customer Experience, and Conversational AI. You will work closely with Delivery, Product, and Engineering teams to review customer interactions, identify issues, perform Root Cause Analysis (RCA), and uncover patterns that impact business outcomes. This is not a role where success is measured by the number of calls reviewed. Success comes from identifying meaningful insights, recurring trends, and opportunities for improvement that help Blue Machines deliver better outcomes for its customers. What You'll Own Call Quality Analysis — Review call recordings and transcripts to identify quality issues, missed objectives, and customer experience gaps. Root Cause Analysis — Investigate conversation failures using transcripts, recordings, workflows, tool outputs, API logs, and internal systems to understand not just what happened, but why. Trend Identification — Track recurring issues by frequency, severity, and business impact to uncover patterns and emerging risks across projects. Funnel Analysis — Analyze customer journeys to identify drop-off points, friction areas, conversion bottlenecks, and failure patterns. Recommendations & Continuous Improvement — Convert findings into actionable insights that improve conversation design, agent performance, operational workflows, and customer outcomes. You don't need prior Voice AI experience. You do need attention to detail, structured thinking, and a genuine interest in understanding how systems, processes, and customer interactions work. The Culture You'll Be Part Of At Blue Machines, quality is everyone's responsibility. We believe problems should be surfaced early, investigated objectively, and solved systematically. Curiosity matters more than hierarchy. Good analysis beats strong opinions. Ownership matters more than blame. If you enjoy digging into data, identifying patterns, and helping teams improve, you'll fit right in. What We're Looking For A natural investigator: when something breaks, your instinct is to understand why, not just document what happened Strong pattern recognition: the ability to look across dozens or hundreds of conversations and identify recurring themes, failure modes, and opportunities for improvement Comfort working with ambiguity: not every problem will have a predefined checklist or obvious answer; you're willing to dig until you find one Curiosity about how systems work: from conversation flows and AI behavior to APIs, integrations, and operational processes Evidence-based thinking: opinions are useful, but conclusions should be supported by data, observations, and structured analysis The ability to learn quickly: Voice AI is evolving rapidly, and the best candidates are comfortable learning new tools, workflows, and concepts as they go Is This You? When something goes wrong, your first instinct is to understand why. You notice patterns that others overlook. You enjoy investigating problems rather than making assumptions. You prefer evidence over opinions. When you find a recurring issue, your instinct is to figure out how often it occurs and how it can be prevented. If that sounds like how you naturally operate, this is probably the right conversation to have. The Opportunity Few internships provide exposure to production AI systems operating at enterprise scale. You'll gain hands-on experience in: Conversational AI, Quality Assurance, Root Cause Analysis, Customer Experience, Funnel Analytics, Operational Excellence Most importantly, you'll learn how to use data and structured thinking to solve real business problems in one of the fastest-growing areas of AI.

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Backend Engineer - SDE 2 (Voice AI / Telephony Platform)

Bengaluru, Karnataka, IN · Onsite · 3 weeks ago

SDE II, Backend — Voice AI & Telephony Experience: 2–4 Years Location: Bengaluru (Work from Office) Team: Blue Machines Role Overview We’re looking for an SDE II (Backend) to help build high-scale, low-latency systems for our AI and voice platform. You’ll work on real-time backend systems that power live voice conversations — combining strong backend fundamentals with exposure to WebRTC, SIP-based telephony, and Voice AI. Responsibilities Build and maintain scalable microservices and backend systems that power real-time AI and voice workflows. Contribute to system design — APIs, data models, deployment, and monitoring — alongside senior engineers. Write performant, concurrent, fault-tolerant code at scale. Implement observability and testing best practices (Datadog, Sentry, etc.). Collaborate with product and AI teams on the platform’s multi-agent orchestration and automation layer. Partner closely with the ML team to integrate in-house models, support benchmarking and observability, and help build the next generation of in-house AI models. Requirements Must-Have Skills 2–4 years of backend development experience in Python or Java. Strong grasp of system design, concurrency, and distributed systems. Experience building scalable APIs or streaming systems. Familiarity with WebRTC, SIP, RTP, or other real-time communication protocols. Experience working with Voice AI or speech processing systems (ASR/TTS, real-time inference). Experience integrating LLMs, vector DBs, or AI agent frameworks into production systems. Experience with cloud environments (GCP/AWS) and containerized deployments (Kubernetes, Docker). Sound understanding of databases (MongoDB, Redis, Postgres) and message queues (Kafka, Pub/Sub). Collaborate with product and AI teams to evolve the platform’s multi-agent orchestration and automation layer .

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Senior QA Automation Engineer

Bengaluru, Karnataka, IN · Onsite · 4 weeks ago

About the role Blue Machines AI builds a production AI agent platform used by large enterprise customers to automate customer interactions at scale — across phone calls, web chat, WhatsApp, and email. The same agent has to hold up whether it's handling a live call, a chat thread, or an email, each with its own failure modes: a voice call breaks on latency and STT/TTS accuracy, a chat session breaks on state and context handling, WhatsApp breaks on message formatting and delivery, email breaks on threading and turnaround. A regression in any of these isn't a broken UI — it's a customer's live support channel going down. We're hiring a Senior QA Engineer to own quality across both the agents themselves and the platform that builds and runs them: the agent builder/configuration flows, workflow orchestration, integrations, and the admin surfaces customers use to manage their agents. You'll build automated coverage for our APIs, services, and agent flows, and go deep on the channel-specific and platform-specific failure modes that a generic QA playbook won't catch. You'll work directly with engineering, not behind a ticket queue, and your calls on release-readiness will carry real weight. What you'll do Design and maintain automated test suites (API, integration, and regression) and wire them into CI/CD so nothing ships without passing them. Build and run test coverage across every channel the agent operates in: voice (call flow, STT/TTS accuracy, latency and timing, degraded network conditions), web chat (state and context handling across turns), WhatsApp (message formatting, delivery, session handling), and email (threading, formatting, response turnaround) — with the same conversation logic and business rules holding up consistently across all of them. Test the platform layer itself, beyond individual agent conversations: agent builder/configuration flows, workflow orchestration, third-party integrations, and the admin/dashboard surfaces customers use to manage and monitor their agents. Drive manual and exploratory testing for new features, new channels, and new platform capabilities before automation coverage exists, with a bias toward finding the edge cases automation won't catch. Write and maintain test plans, test cases, and bug reports with enough evidence and reproducibility that engineering can act on them without back-and-forth. Partner with engineering on release sign-off — you're expected to have and defend an opinion on whether a release is safe to ship. Set up and improve monitoring/alerting signals that catch quality regressions in production, not just pre-release. Mentor and raise the testing bar across the team as we grow QA from an individual function into a practice. What we're looking for 4–6 years in QA/SDET roles, with real ownership of both manual and automated testing — not just executing a fixed test suite. Hands-on experience with test automation frameworks (e.g., Selenium, Playwright, or Cypress) and API testing tools (Postman, REST-assured, or similar). Working knowledge of CI/CD pipelines and integrating automated tests into them (Jenkins, GitHub Actions, GitLab CI, or similar). Experience testing conversational or multi-channel systems — any combination of voice/IVR, chat/messaging platforms, or email-based workflows — and the judgment to reason about failure modes in channels or platform surfaces (builders, rules engines, integrations) you haven't tested before. Comfort reading logs/traces to root-cause a failure rather than just filing "doesn't work." Basic scripting ability (Python or JavaScript) to build test tooling, not just consume it. Clear written communication — your bug reports and test plans need to hold up without you in the room. Nice to have Direct experience testing STT/TTS pipelines, WhatsApp Business API integrations, or conversational AI/LLM-based products. Familiarity with SIP, telephony carrier integrations, or call quality metrics (jitter, packet loss, MOS scores). Experience with performance/load testing tools (k6, JMeter, Locust). Prior experience setting up a QA function or automation practice from scratch. Why Blue Machines You'll help shape how quality gets built into a fast-moving, multi-channel AI agent platform — with real ownership over what ships, working directly alongside the engineers building it.

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Forward Deployed Engineer (AI Integration + Design) Gen AI & Voice AI - US Shift

Bengaluru, Karnataka, IN · Onsite · 2 months ago

Role Overview As a Forward Deployed Engineer, you’ll design, build, and support integrations between the Blue Machines platform and client systems. You’ll work across APIs, cloud services, and AI frameworks (like LangChain and LLM APIs) to deliver intelligent, reliable, and production-grade integrations. Responsibilities • Develop and maintain integrations using REST APIs, WebSockets, and webhooks • Build and deploy solutions leveraging cloud platforms (GCP / AWS / Azure) • Integrate with AI/LLM frameworks such as LangChain, OpenAI, or similar SDKs • Collaborate with client and internal teams for deployment, debugging, and optimization • Automate, document, and maintain integration workflows and observability Requirements • Experience in Python or Java development for backend and integrations • Mandatory hands-on experience with cloud platforms (preferably GCP) • Strong understanding of web technologies, APIs, and authentication protocols (OAuth2, JWT) • Familiarity with AI/LLM ecosystems, prompt design, or LangChain-style orchestration • Excellent problem-solving and client communication skills Nice to Have • Experience with telephony and real-time communication (SIP, WebRTC, Twilio, Avaya, Ubona) • Familiarity with Postman, Wireshark, or observability tools • Understanding of CI/CD pipelines and containerized deployments Work Timings • US Shift

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AI Product & Evals Analyst (Voice Agents)

Bengaluru, Karnataka, IN · Onsite · 4 months ago

Company: Bluemachines.ai Location: Bangalore / 5 days WFO Experience: 3–4 years Function: Analytics Role Summary We’re hiring an AI AI Product & Evals Analyst Analyst to own evaluation, quality measurement, dashboarding, and enterprise analytics for Bluemachines’ AI voice agents. You will work at the intersection of AI Engineering, Product, and Customer Delivery to define how voice agent quality is measured, monitored, and improved at scale. This includes building evaluation frameworks, detecting regressions, analyzing business impact, and enabling enterprise teams with clear, actionable insights. Beyond evaluation, we’re looking for someone with an AI-first mindset who can leverage modern AI tools and automation workflows to improve analytics, reporting, and operational efficiency. The role will also contribute toward building reusable analytics frameworks, internal intelligence tooling, and self-serve analytics capabilities for enterprise clients. Your work will directly influence launch quality, customer trust, operational transparency, and how enterprise AI systems are measured and scaled. What will you do? Business & Enterprise Analytics Track and analyze business KPIs tied to voice agent deployments (automation, containment, conversion, CSAT, cost savings, etc.) Support enterprise billing, audit, and reconciliation workflows through reliable usage and conversation analytics Translate AI behavior into clear operational and business impact insights for enterprise clients AI-First Analytics & Automation Leverage AI tools and agentic workflows to improve speed, quality, and scalability of analytics, reporting, and RCA workflows Automate repetitive analytics and reporting tasks using LLMs, copilots, and workflow tooling Drive AI-native ways of working across SQL, Python, dashboards, and insight generation Analytics Platform & Internal Tooling Build reusable analytics frameworks, standardized dashboards, and internal tooling for enterprise deployments Contribute to self-serve analytics and intelligence capabilities such as text-to-data, AI-powered insights, and conversational analytics interfaces Help evolve Bluemachines’ analytics and observability layer for enterprise AI voice agents Voice Agent Evaluation Design and own AI eval frameworks specifically for voice agents Define conversation- and turn-level metrics Build and maintain golden voice datasets across accents, languages, and noise conditions What We’re Looking For Must-Have 2–5 years of experience in Product Analytics, Data Analytics, AI Quality, or related analytical roles Strong analytical thinking, metric design, and problem-solving skills Hands-on proficiency in SQL and Python for analysis, evaluation, and data investigation Ability to reason deeply about conversational, voice, and workflow-driven systems Experience building dashboards and enterprise-grade visualizations using tools like Tableau, Power BI, Looker, or equivalent Strong communication and storytelling skills with the ability to translate AI/system behavior into business insights Comfort working cross-functionally with AI Engineering, Product, Operations, and customer-facing teams AI-first mindset with strong adoption of modern AI tools, copilots, and automation workflows to improve productivity and scale analytics Good-to-Have Experience with voice systems such as STT, TTS, call analytics, or conversational AI platforms Exposure to LLM-based products, prompt engineering, AI evals, or agentic workflows Experience with enterprise analytics, client-facing reporting, billing/reconciliation, or operational analytics Interest in building internal analytics tooling, reusable frameworks, or self-serve intelligence systems Experience working in fast-moving AI or startup environments

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Enterprise Marketing Manager

Bengaluru, Karnataka, IN · Onsite · 6 months ago

Description Website: https://bluemachines.ai/ Enterprise Voice AI Orchestration Platform, Made in India; For the World Who we are Blue Machines AI is an enterprise-grade Voice AI platform for deploying reliable, compliant, low-latency, multilingual voice agents at scale. We focus on one thing: making Voice AI truly production-ready for high-stakes enterprise workflows, not just demos. Our platform orchestrates speech-to-text, text-to-speech, and a coordinated council of large language models, backed by carrier-grade infrastructure. We pair the platform with Forward Deployment Engineers to help enterprises go live in days, not months, and operate confidently at scale. Vision As work evolves into a blend of human talent and AI agents, Blue Machines AI is building the trust layer enterprises will rely on. Our goal is to make Voice AI as dependable as any critical enterprise system: capable, responsible, and always in service of human primacy. Requirements Enterprise Marketing Manager - (B2B Events) Location: Bengaluru, India (In-Office) Experience: 2-5 years Department: Brand & Marketing Job Summary As the Enterprise Event Marketing Manager at Blue Machines AI, you will build and run experiences that move the pipeline. You will deliver flagship events and executive roundtables designed to accelerate enterprise deals. You will partner closely with Sales to set clear commercial goals for every activation, and drive disciplined follow-through with measurable ROI. This is an end-to-end ownership role that blends operational rigor with creative instinct. Key Responsibilities Flagship Events & Roundtables Own end-to-end planning and execution of flagship events: venue, agenda, speaker curation, logistics, and reporting. Plan and run executive roundtables to build relationships and accelerate deal cycles with enterprise decision-makers. Create event briefs, run-of-show documents, and post-event impact reports for each activation. Pipeline & Sales Enablement Partner with Sales and GTM to define event objectives tied directly to pipeline outcomes. Build pre-event outreach and post-event follow-up sequences to convert attendees into opportunities. Track and report ROI: qualified leads, pipeline influenced, and deals accelerated. Operations & Vendor Management Own vendor partnerships across venue, AV, production, catering, and event tech. Manage budgets tightly and deliver premium experiences within cost targets. Build repeatable playbooks and checklists to scale the program with consistent quality. Content & Amplification Coordinate with Brand and Video teams to capture and distribute event content across channels. Create post-event content loops (highlights, takeaways, speaker clips) to extend impact beyond the room. Requirements Experience 3 to 5 years in B2B event marketing, field marketing, or conference management (tech/SaaS preferred). Proven track record of events that drove measurable pipeline outcomes, not just attendance. Strong cross-functional experience with Sales, Marketing, and leadership teams. Skills Strong project/program management across multiple parallel workstreams. Strong vendor negotiation and stakeholder management. Data-driven: comfortable defining KPIs, reporting, and improving future activations. Willingness to travel for flagship events across India. Benefits What We Offer Full ownership of the events program at a high-growth enterprise AI company. Direct collaboration with senior leadership and Sales on high-stakes activations. Exposure to enterprise GTM at a company shaping a new category. Competitive compensation aligned to market benchmarks. High-ownership environment with visible, measurable impact.

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