{"id":714825,"url":"https://alion.io/job/withdavid-research-scientist","title":"Research Scientist","company":{"id":673490,"name":"David AI Labs","domain":"withdavid.ai","url":"https://alion.io/company/withdavid","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":75,"open_postings":6,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-02T06:13:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":210000,"max":360000,"currency":"USD","period":"year","gross":null,"usd_annual":360000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scale AI","optional":false}],"status":"live","first_seen_at":"2026-05-15T17:07:11Z","employer_posted_date":"2026-05-15","last_verified_at":"2026-11-02T14:01:10Z","board_verified":true,"closed_at":null,"days_open":170,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":170},"description":"About David AI\nDavid AI is the first audio data research company. We bring an R&D approach to data-developing datasets with the same rigor AI labs bring to models. Our mission is to bring AI into the real world, and we believe audio is the gateway. Speech is versatile, accessible, and human-it fits naturally into everyday life. As audio AI advances and new use cases emerge, high-quality training data is the bottleneck. This is where David AI comes in.\nDavid AI was founded in 2024 by a team of former Scale AI engineers and operators. In less than a year, we’ve brought on most FAANG companies and AI labs as customers. We recently raised a $50M Series B from Meritech, NVIDIA, Jack Altman (Alt Capital), Amplify Partners, First Round Capital and other Tier 1 investors.\nOur team is sharp, humble, ambitious, and tight-knit. We’re looking for the best research, engineering, product, and operations minds to join us on our mission to push the frontier of audio AI.\nAbout our Machine Learning team\nOur Machine Learning team sits at the intersection of cutting-edge research and production systems, transforming raw audio into high-signal data for leading AI labs and enterprises. We own the full ML lifecycle - from researching novel speech processing algorithms to deploying models processing terabytes of audio daily.\nAbout this role\nAs a Research Scientist at David AI you'll build cutting-edge speech and audio models, production inference systems and resilient pipelines that showcase what high-quality data can really do.\nIn this role, you will\nResearch, design, and implement solutions using signal processing, algorithms and cutting edge ML models with application to speech and audio.\n\nDevelop production-grade inference algorithms, pipelines, and APIs with cross-functional teams that unlock key insights into our data for our customers.\n\nCollaborating with our Operations team to gather useful training and evaluation datasets to improve the quality of our models.\n\nArchitect systems that enable resilient, durable inference and evaluations.\n\nYour background looks like\n5+ years of professional audio ML experience, including DSP and ML audio algorithm development.\n\nEnd-to-end ownership of ML pipelines, from proof-of-concept to production deployment.\n\nStrong coding skills in Python and proficiency with deep learning frameworks such as PyTorch.\n\nAbility to translate research papers and ideas into high-quality, production-ready code.\n\nExperience deploying ML systems for production inference with cloud technologies.\n\nTrack record of setting ML roadmaps, influencing technical direction, and prioritizing research and infrastructure investments.\n\nAbility to assess model quality in the context of user experience and business value.\n\nBonus points if you have\nPhD or Masters in Computer Science or a related field.\n\nExperience training large neural network models in academic or industry settings.\n\nExpertise in audio signal processing both classical and machine learning techniques.\n\nExperience in publishing in top conferences such as NeurIPS, ICML, ICLR, CVPR, etc.\n\nBenefits\nUnlimited PTO.\n\nTop-notch health, dental, and 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