Machine Learning Scientist, Reinforcement Learning
Profluent · Emeryville, California, United States; Hybrid (2-3 days on-site)
Posted about 2 months ago
or apply directly on Profluent's site. We never take the application ourselves.
Is this posting real?
- This role has been open
- 63 days Profluent's roles stay open a median of 63 days
- Reposted
- No
- Salary listed
- No 0% of Profluent's roles list one
- Ghost-job risk at Profluent
- high 12 stale, 0 reposted of 12 open
- Hiring momentum
- 17 roles opened in the last 90 days ↑ up vs. the prior 90 days
- Last confirmed on the employer's board
- 2026-10-05
Measured from postings appearing on and disappearing from Profluent's own greenhouse board since 2026-08-03. Full hiring picture for Profluent.
About this role
As a Machine Learning Scientist focused on reinforcement learning at Profluent, you will conduct research to develop and optimize algorithms for protein design. Your role involves collaborating with interdisciplinary teams, prototyping new models, and evaluating generative models in the biomolecular domain. You will also curate datasets and present your findings to colleagues, shaping the scientific direction of the company.
- benefits
- 3/5
- freshness
- 1/5
- career value
- 5/5
- role clarity
- 5/5
- pay transparency
- 0/5
Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of Profluent as an employer.
What you need
- PhD (or equivalent industry experience) in Computer Science, Machine Learning, Natural Language Processing, Applied Math, Computational Biology, Statistics, or a related field
- Experience with conceiving of, implementing, and evaluating novel machine learning and reinforcement learning techniques
- Publications at major machine learning conferences (NeurIPS, ICML, ICLR) or scientific journals (Nature, Science, Nature Biotech, Nature Methods, PNAS)
- Experience with modern deep learning frameworks such as Pytorch or Jax
Nice to have
- Familiarity with foundational biology of proteins and nucleic acids
- Experience developing machine learning models for proteins (language models, structure prediction, design)
- Experience with cloud compute platforms (GCP, AWS, Azure, OCI)
- Previous experience in data extraction and curation from bioinformatics data sources
- Familiarity with wet lab experimental assays and associated limitations
What you get
- High-growth opportunity with meaningful impact on the future of protein design
- Competitive compensation package with equity participation
- 401(k) with a strong employer match
- Comprehensive benefits including health/dental/vision insurance
- Generous PTO policy and commitment to work-life balance
- Professional development opportunities in a cutting-edge field at the intersection of AI and biology
Worth weighing
- No specific mention of remote work flexibility beyond hybrid model (2-3 days on-site)
- The role is positioned at an early-stage company, which may involve uncertainty and rapid changes
- Salary range is provided but could vary based on experience and negotiation
Summarised from Profluent's posting. Read the full original.
Listed by Profluent on their greenhouse job board, last confirmed open on 2026-10-05. PitchMeAI is not the employer.
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