Machine Learning Research Engineer
Profluent Bio — Tracked from its greenhouse job board
About the role
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.
We're looking for an experienced Machine Learning Engineer to build and improve the models and ML systems that drive our protein design efforts. In this role, you'll deploy and optimize large-scale generative models for protein design, and develop the surrounding infrastructure and tooling that enable our ML and protein design scientists to work faster and more confidently. As an early member of a small, fast-moving engineering team, you'll have significant ownership over our ML stack and the opportunity to shape how our platform evolves.
Responsibilities
Build robust, reproducible and user-friendly pipelines for automated model fine-tuning, alignment and evaluation
Design and implement modular, easy-to-maintain, multi-model pipelines for protein design
Develop highly scalable ETL pipelines to process petabyte-scale protein data for model pretraining
Optimize model training and inference code to maximize throughput and resource utilization when deployed at scale
Develop software and infrastructure that enable the ML team to work quickly and frictionlessly in distributed and multi-cloud environments
Partner with ML and protein design scientists to prototype research ideas and bring them into production
Who You Are
You're comfortable taking ownership and working independently in a fast-moving environment
You're an execution-oriented engineer who maintains high standards, and focuses on the highest-impact work
You're comfortable owning the full stack of your work, from training code to the infrastructure it runs on
You care deeply about model quality, efficiency, and reliability
You're willing to step beyond your core responsibilities when the team needs it
Representative Projects
Building hyperparameter search frameworks for SFT and Alignment workflows
Increasing protein language model throughput during long context generation
Updating existing model architectures to work and run efficiently on new GPU hardware
Implementing a protein design pipeline that integrates prompt retrieval, sequence generation, attribute prediction, and structure prediction
Establishing an ETL pipeline for sampling and tokenizing training datasets from an internal database of billions of sequences
Developing a benchmarking and evaluation system for newly trained sequence generation models
Contributing to the development of an internal service that provides transparent multi-node job submission for ML scientists
Qualifications
BS or MS in Computer Science, Machine Learning, or a related field
3+ years of hands-on experience building and training ML models in PyTorch
Strong Python and software engineering fundamentals, including testing, code quality, and version control
Experience profiling, benchmarking, and optimizing ML model training and inference
Experience implementing or optimizing transformer-based architectures
Familiarity with cloud infrastructure and containerization (GCP, AWS, Azure, Kubernetes, Docker)
Strong fundamentals in ML, statistics, and/or linear algebra
Preferences
Familiarity with protein language models or computational biology
Experience with GPU-level optimization (CUDA, Triton)
Experience with distributed training (DDP, FSDP, multi-node GPU clusters)
Experience with databases and data processing pipelines
Experience orchestrating multi-step ML workflows
Experience building backend systems that serve ML models in production
Contributions to open source ML projects or published research
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.
Hiring Salary Range
$200,000 $330,000 USD
What the index says about this role
- First seen by JobLarper — Aug 2, 2026, 6 days ago. Older postings collect hundreds of applicants — a tailored résumé matters more the longer a role has been live.
- No pay range in our index for this listing. Across 193 indexed Machine Learning Engineer roles in US that do publish one, the middle half sits between $213k and $300k, median $250k — JobLarper's read of the market, not a figure from Profluent Bio.
- What Machine Learning Engineer roles ask for — across 1,108 indexed openings: ML (78%), AI/LLM (55%), Python (53%), REST/APIs (38%), Cloud (25%). This posting names ML, AI/LLM, Python, Cloud, Backend.
- Profluent Bio is hiring actively — 7 open roles indexed.
Derived from the 27,000 roles JobLarper indexes daily from official company boards — not from the job description above.
More open roles at Profluent Bio
- Machine Learning Scientist, PretrainingEmeryville, California, United States; Hybrid (2-3 days on-site) · Mid
- Scientist II, ML - Guided Protein Design EvaluationEmeryville, California, United States; Hybrid (2-3 days on-site) · Junior
- Machine Learning Scientist, BioMLEmeryville, California, United States; Hybrid (2-3 days on-site) · Mid
- Machine Learning Scientist, Reinforcement LearningEmeryville, California, United States; Hybrid (2-3 days on-site) · Mid
- Senior Software Engineer, Data PlatformEmeryville, California, United States; Hybrid (2-3 days on-site) · Senior+
- Software Engineering Manager, Lab Informatics PlatformEmeryville, California, United States; Hybrid (2-3 days on-site) · Manager
All 7 open roles at Profluent Bio →
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