Machine Learning Engineer

Profluent • Emeryville, CA

3h • Onsite

About The Position

Profluent is an AI-first protein design company founded in 2022. We develop deep generative models to design and validate novel, functional proteins to revolutionize biomedicine. Based in Emeryville, CA, we are backed by leading investors and have raised over $150M to date. We are 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 will 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 will have significant ownership over our ML stack and the opportunity to shape how our platform evolves.

Requirements

• 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
• Legal authorization to work in the United States is required.

Nice To Haves

• 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

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

Benefits

• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Associate degree