{"id":1996412,"url":"https://alion.io/job/google-senior-research-scientist-ml-foundations","title":"Senior Research Scientist, ML Foundations","company":{"id":82,"name":"Google","domain":"google.com","url":"https://alion.io/company/google","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"B","score":75,"open_postings":108,"ghost_share":0,"stale_share":0.981,"repost_share":0,"time_to_fill_p50_days":30,"computed_at":"2026-10-19T05:45:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":159000,"max_usd":304000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1213},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"TensorFlow","optional":false},{"name":"Reinforcement Learning","optional":true}],"status":"live","first_seen_at":"2026-10-07T06:37:17Z","employer_posted_date":"2026-10-07","last_verified_at":"2026-10-20T03:04:35Z","board_verified":true,"closed_at":null,"days_open":12,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":12},"description":"About the job\nAs an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.As a Research Scientist, you'll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.Google Research is building the next generation of intelligent systems for all Google products. To achieve this, we’re working on projects that utilize the latest computer science techniques developed by skilled software developers and research scientists. Google Research teams collaborate closely with other teams across Google, maintaining the flexibility and versatility required to adapt new projects and foci that meet the demands of the world's fast-paced business needs.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.\nUS: $174000 - $252000 (USD) + 15% bonus target + equity + benefits\nLearn more about benefits at Google.\nResponsibilities\nConduct research in Machine learning, e.g., derive theoretical insights, develop alogrithm prototypes and evaluate them on academic and internal benchmarks.\nCommunicate research findings with the external community through publications at top ML venues and internal stakeholders through tech reports and presentations.\nDevelop approaches for more robust simulator learning and productionize them to improve driving simulation models for Waymo.\nPartner with Waymo, and other Product Areas, to turn insights from algorithmic research and proof-of-concept implementations into product improvements.\nQualifications\nMinimum qualifications:\nPhD in Computer Science, Artificial Intelligence, Machine Learning, a related field, or equivalent practical experience.\n2 years of experience with research in machine learning or a related field, with publications at ML conferences (e.g., ICML, NeurIPS, ICLR)\nExperience with ML algorithm and model implementation in Python.\nExperience with deep learning frameworks (TensorFlow, Jax or others).\nPreferred qualifications:\n1 year of experience owning and initiating research agendas.\nExperience with reinforcement learning research and applications.\nExperience in deep learning and distributed training.\nTrack record of developing ML solutions for real world 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