{"id":128001,"url":"https://alion.io/job/profluent-machine-learning-scientist-reinforcement-learning","title":"Machine Learning Scientist, Reinforcement Learning","company":{"id":48175,"name":"Profluent","domain":"profluent.bio","url":"https://alion.io/company/profluent","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"A","score":90,"open_postings":11,"ghost_share":0,"stale_share":0.182,"repost_share":0,"time_to_fill_p50_days":96,"computed_at":"2026-10-16T05:45:00Z"}},"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":"explicit","locations":["Emeryville, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":212000,"max":339000,"currency":"USD","period":"year","gross":null,"usd_annual":339000},"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":"Machine Learning","optional":false},{"name":"Post-training","optional":false},{"name":"PyTorch","optional":false},{"name":"Reinforcement Learning","optional":false}],"status":"live","first_seen_at":"2026-06-02T23:51:17Z","employer_posted_date":"2026-09-11","last_verified_at":"2026-10-17T00:26:09Z","board_verified":true,"closed_at":null,"days_open":136,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":135},"description":"Profluent is the frontier AI lab for biology. Profluent builds powerful foundation models for all of life's molecules, unlocking solutions that transform medicine, agriculture, and beyond. Founded in 2022 and headquartered in Emeryville, CA, Profluent is backed by leading investors including Altimeter Capital, Bezos Expeditions, Spark Capital, Insight Partners, Air Street Capital, AIX Ventures, and Convergent Ventures and has raised over $150M to date.\nWe're looking for a motivated and creative Machine Learning (ML) Scientist to drive research into reinforcement learning for biomolecular design. This position offers an opportunity to work at the forefront of generative modeling research across language processing, representation learning, and protein engineering. You should be a self-directed researcher who has the ability to rapidly prototype and evaluate new models and algorithms in the biomolecular domain.\nAs an early employee, you will proactively shape the direction of our machine learning efforts and collaborate across diverse teams of computational and experimental scientists.\nResponsibilities\nDesign and develop state-of-the-art online and offline reinforcement learning algorithms for protein design\nCollaborate across the machine learning and protein design teams to adapt and improve reinforcement learning techniques from other domains to protein design\nArchitect, implement, and optimize core infrastructure to support the post-training of protein language models\nCurate relevant datasets and design tasks for rigorous evaluation of generative models\nImplement, analyze, and interpret multiple computational approaches and present results to colleagues in regular update meetings\nWork within a collaborative, fast-paced, interdisciplinary team across biology and machine learning to help shape the scientific and strategic vision of the company\nQualifications\nPhD (or equivalent industry experience) in Computer Science, Machine Learning, Natural Language Processing, Applied Math, Computational Biology, Statistics, or a related field\nExperience with conceiving of, implementing, and evaluating novel machine learning and reinforcement learning techniques\nPublications at major machine learning conferences (NeurIPS, ICML, ICLR) or scientific journals (Nature, Science, Nature Biotech, Nature Methods, PNAS)\nExperience with modern deep learning frameworks such as Pytorch or Jax\nPreferences\nFamiliarity with foundational biology of proteins and nucleic acids\nExperience developing machine learning models for proteins (language models, structure prediction, design)\nExperience with cloud compute platforms (GCP, AWS, Azure, OCI)\nPrevious experience in data extraction and curation from bioinformatics data sources\nFamiliarity with wet lab experimental assays and associated limitations\nWhat We Offer\nHigh-growth opportunity with meaningful impact on the future of protein design\nCompetitive compensation package with equity participation\n401(k) with a strong employer match\nComprehensive benefits including health/dental/vision insurance\nGenerous PTO policy and commitment to work-life balance\nProfessional development opportunities in a cutting-edge field at the intersection of AI and biology\nProfluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.\nEmployment Eligibility Verification\nLegal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.\nHiring Salary Range\n$212,000—$339,000 USD\nNOTICE TO STAFFING AND SEARCH FIRMS: Profluent does not accept unsolicited candidate submissions. We ask that agencies refrain from sending resumes to our careers inbox, hiring managers, or any Profluent employee. 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