We'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.

As an early employee, you will proactively shape the direction of our machine learning efforts and collaborate across diverse teams of computational and experimental scientists.

Responsibilities

• Design and develop state-of-the-art online and offline reinforcement learning algorithms for protein design
• Collaborate across the machine learning and protein design teams to adapt and improve reinforcement learning techniques from other domains to protein design
• Architect, implement, and optimize core infrastructure to support the post-training of protein language models
• Curate relevant datasets and design tasks for rigorous evaluation of generative models
• Implement, analyze, and interpret multiple computational approaches and present results to colleagues in regular update meetings
• Work within a collaborative, fast-paced, interdisciplinary team across biology and machine learning to help shape the scientific and strategic vision of the company

Qualifications

• 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

Preferences (but not required)

• 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 We Offer

• 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

Profluent 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.

Employment Eligibility Verification

Legal 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.