{"id":3879280,"url":"https://alion.io/job/josh-talks-forward-deployed-ai-ml-engineer","title":"Forward Deployed AI / ML Engineer","company":{"id":2421066,"name":"Josh Talks","domain":"joshtalks.com","url":"https://alion.io/company/joshtalks","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Darwinbox","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Gurgaon, 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":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"GCP","optional":false},{"name":"Hugging Face","optional":false},{"name":"LLM","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Rest API","optional":false},{"name":"Speech Recognition","optional":false},{"name":"Text-to-Speech","optional":false},{"name":"Voice Agents","optional":false},{"name":"WebSockets","optional":false},{"name":"Fine-tuning","optional":true},{"name":"NVIDIA NeMo","optional":true},{"name":"Whisper","optional":true}],"status":"live","first_seen_at":"2026-11-06T17:22:15Z","employer_posted_date":null,"last_verified_at":"2026-11-06T17:22:15Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"Forward Deployed AI / ML Engineer — Evaluations (Product + Engineering)\nWebsite: ai.joshtalks.com and voicearena.com\nLocation: Gurugram\n\nAbout us\nJosh Talks AI builds and licenses audio datasets to leading AI labs. We've been deliberately quiet for the last year and just built. The product has earned the right to be expanded; we are now hiring the people who will own what gets built next.\n\nAbout the role\nThis is an Evaluations PM + Engineer role. You will own how we measure the quality of our speech, voice, and image data, and of our customers models: ASR, TTS, speech-to-speech (S2S), and voice agents. You will define what good means for each dataset and model, build and run the evaluations yourself, and turn the results into clear decisions for the product, research, and business teams.\nYou don't hand evaluations off. You plan them, run them end to end, and own the outcome.\n\nWhat you'll do\nEvaluation product ownership\nOwn the evaluation roadmap across ASR, TTS, S2S, and voice-agent models.\nWork with research, product, and business teams to understand use cases and define what quality means for each one.\nTurn quality goals into clear evaluation plans: test sets, metrics, pass/fail thresholds, and timelines.\nPrioritise which models, languages, and use cases to evaluate first, based on impact.\nShare results through clear reports and dashboards, and make go/no-go recommendations on model releases.\nTrack model quality over time and flag regressions early.\n\nHands-on evaluation (done by you)\nRun end-to-end evaluations of ASR, TTS, S2S, and voice-agent models yourself.\nSet up and run open-source and in-house models locally and on cloud GPUs for inference.\nIntegrate and run models from different vendors and customers through their APIs (batch and streaming), and compare them fairly.\nManage cloud GPU instances (GCP/AWS/Azure) to run large-scale evaluation and inference jobs efficiently.\nBuild and curate evaluation datasets, including multilingual, Indian-language, noisy, and real-world audio.\nDesign and run human evaluations: listening tests, rating guidelines, annotator training, and agreement checks.\nWrite reproducible evaluation pipelines in Python and automate recurring benchmarks.\nAnalyse errors to find failure patterns and feed them back to the research and data teams.\nBenchmark in-house models against third-party and open-source models.\n\nWhat we're looking for\nSkills\nHands-on evaluation of ASR, TTS, S2S, or voice/LLM agent models.\nStrong Python, with Pandas/NumPy, Hugging Face, and audio libraries (librosa, torchaudio).\nRunning ML model inference (PyTorch / Hugging Face) on GPUs.\nWorking with third-party model APIs (REST, WebSocket/streaming).\nCloud platforms (GCP, AWS, or Azure), including GPU instances.\nEvaluation metrics, test-set design, and statistical significance.\nDesigning human evaluation studies and rating guidelines.\nClear written and verbal communication, and explaining results to technical and non-technical people.\nStrong ownership, and the ability to work independently in a fast-moving team.\n\nNice to have\nExperience fine-tuning speech models (ASR, TTS, or S2S).\nExperience with Indian languages, code-mixed, or low-resource speech data.\nFamiliarity with Whisper, NeMo, pyannote, ESPnet, or commercial speech APIs.\nExperience evaluating LLMs or voice agents (ASR → LLM → TTS pipelines).\nExperience building evaluation dashboards or automated regression testing.\n\nWhy join us\nOwn how quality is defined and measured for speech AI used at scale.\nWork closely with research and product, and directly shape which models ship.\nHigh ownership and real impact from day 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