{"id":1388972,"url":"https://alion.io/job/blue-machines-ai-ml-research-engineer-speech","title":"ML Research Engineer, Speech","company":{"id":2943,"name":"Blue Machines AI","domain":"bluemachines.ai","url":"https://alion.io/company/blue-machines-ai","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"A","score":90,"open_postings":5,"ghost_share":0,"stale_share":0.4,"repost_share":0,"time_to_fill_p50_days":34,"computed_at":"2026-11-01T06:10:25Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Hugging Face","optional":false},{"name":"ISO 27001","optional":false},{"name":"MLFlow","optional":false},{"name":"NVIDIA NeMo","optional":false},{"name":"ONNX","optional":false},{"name":"Pre-training","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Self-Supervised Learning","optional":false},{"name":"SOC 2","optional":false},{"name":"TensorRT","optional":false},{"name":"Text-to-Speech","optional":false},{"name":"Tokenization","optional":false},{"name":"Transformers","optional":false},{"name":"Weights & Biases","optional":false},{"name":"Fine-tuning","optional":true},{"name":"LLM","optional":true},{"name":"LoRA","optional":true},{"name":"PEFT","optional":true},{"name":"SFT","optional":true},{"name":"WebRTC","optional":true}],"status":"live","first_seen_at":"2026-09-28T11:10:47Z","employer_posted_date":"2026-09-28","last_verified_at":"2026-11-01T09:31:20Z","board_verified":true,"closed_at":null,"days_open":34,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":34},"description":"About Blue Machines and the Speech Research Team\nBlue 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.\nWe 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.\nWhat makes this work different\nReal traffic: your model ships to live enterprise calls, not a leaderboard\nHard problems: 8 kHz telephony audio, Hinglish and code-switching, accents, noisy environments, domain entities (loan numbers, policy IDs, names)\nTight latency budgets: streaming inference where every 50 ms is noticed by callers\nA full loop: data, training, evaluation, serving and production feedback in one team\nLocation: Bengaluru (on-site / hybrid) · Team: Speech Research, reporting into the CTO org\nRole 1: ML Research Engineer, Speech (1-3 years)\nYou 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.\nWhat you will do\nPre-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\nTrain TTS models from scratch (flow-matching, diffusion, neural codec LMs, vocoders) and extend them to new voices, languages and speaking styles\nBuild speech-to-speech components from scratch: audio tokenizers and codecs, speech encoders connected to LLMs, streaming decoders\nTurn papers and new ideas into working PyTorch code: write the model, tokenizer and training loop yourself, and train from random initialisation\nBuild data pipelines: cleaning, segmentation, forced alignment, pseudo-labelling, augmentation (noise, codecs, 8 kHz telephony simulation)\nMaintain evaluation suites: WER/CER, entity error rate, code-switch accuracy, MOS and speaker similarity, latency (time to first token / byte)\nOptimise models for serving: quantisation, streaming chunking, ONNX/TensorRT export, batching on GPUs\nAnalyse production errors, turn them into test sets, and close the loop with the platform team\nWrite clear experiment reports and share findings in weekly research reviews\nWhat you bring\n1-3 years in ML, with at least one real project in speech or audio (industry, research lab, or a strong thesis)\nB.Tech/M.Tech/MS in CS, EE or a related field; a PhD is not required\nStrong Python and PyTorch; able to implement a model architecture and training loop from scratch, not just call APIs or fine-tune checkpoints\nWorking knowledge of speech basics: spectrograms, MFCC/mel features, CTC, attention-based seq2seq, vocoders\nHands-on with at least one of: NeMo, ESPnet, Hugging Face Transformers/Audio, fairseq, Coqui, k2/icefall\nHas trained at least one model from random initialisation (speech, audio or language), including multi-GPU jobs, mixed precision and experiment tracking (W&B, MLflow)\nCareful with evaluation: you know why a WER number can mislead, and you check your data\nNice to have\nSpeak or understand Hindi or another Indian language\nPublications, Kaggle/benchmark results, or open-source contributions in speech\nExposure to real-time audio (WebRTC, SIP, streaming inference) or telephony audio\nFamiliarity with LLM fine-tuning (LoRA, SFT) or audio-language models\nWhat success looks like in 6 months\nContributed to a pre-trained-from-scratch model that shipped to production with a measured gain on a customer-relevant test set\nOwns a piece of the evaluation or data pipeline that others rely on\nRuns experiments independently and reports results the team can trust","description_format":"text","description_chars":4196,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[{"language":"Hindi","level":"All levels","optional":true}]},"benefits":[],"hiring_locations":[{"name":"India","iso":"IN","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Conversational AI","Speech & Audio AI","AI Agents"],"lifecycle":[{"event":"open","at":"2026-09-28T11:10:47Z"}],"visa":[],"liveness":{"score":52,"band":"ok","label":"Likely open","p_open":1,"p_active":0.692,"p_room":0.75,"age_days":33,"expected_fill_days":34,"reasons":["conf:0","velocity","win:late"],"computed_at":"2026-11-01T06:10:25Z"},"pay":null,"html_url":"https://alion.io/job/blue-machines-ai-ml-research-engineer-speech","json_url":"https://alion.io/job/blue-machines-ai-ml-research-engineer-speech.json","meta":{"generated_at":"2026-11-01T12:38:00Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":19437,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-02T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":2943},"rest":"https://alion.io/mcp/rest/get_company?id=2943"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fblue-machines-ai-ml-research-engineer-speech"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fblue-machines-ai-ml-research-engineer-speech"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fblue-machines-ai-ml-research-engineer-speech"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/blue-machines-ai-ml-research-engineer-speech\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fblue-machines-ai-ml-research-engineer-speech"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":1388972}},{"tool":"search_jobs","arguments":{"company":"bluemachines.ai","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":1388972},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); 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