Machine Learning Research Engineer (Protein Design)

Location: Emeryville, California, United States; hybrid with 2–3 days on-site. Legal authorization to work in the United States is required.

Hiring salary range: $200,000–$330,000 USD per year, plus equity participation.

Company

hirify.global is a frontier AI lab building foundation models for biological molecules and protein design applications in medicine, agriculture, and related fields.

What you will do

• Build reproducible pipelines for model fine-tuning, alignment, evaluation, and benchmarking.
• Design modular multi-model pipelines for protein design, integrating retrieval, sequence generation, attribute prediction, and structure prediction.
• Develop petabyte-scale ETL pipelines for sampling and tokenizing protein training datasets.
• Optimize model training and inference for throughput, resource utilization, and new GPU hardware.
• Build ML infrastructure and tooling for distributed and multi-cloud environments, including transparent multi-node job submission.
• Partner with ML and protein design scientists to prototype research ideas and bring them into production.

Requirements

• BS or MS in Computer Science, Machine Learning, or a related field.
• 3+ years of hands-on experience building and training ML models with PyTorch.
• Strong Python and software engineering fundamentals, including testing, code quality, and version control.
• Experience profiling, benchmarking, and optimizing ML training and inference, including transformer-based architectures.
• Familiarity with cloud infrastructure and containerization, including GCP, AWS, Azure, Kubernetes, or Docker.
• Strong fundamentals in machine learning, statistics, and/or linear algebra.

Nice to have

• Protein language models or computational biology experience.
• GPU-level optimization with CUDA or Triton and distributed training with DDP, FSDP, or multi-node GPU clusters.
• Experience with databases, data processing pipelines, and multi-step ML workflow orchestration.
• Experience building backend systems that serve ML models in production.
• Open-source ML contributions or published research.

Culture & Benefits

• High-growth opportunity focused on protein design and AI-driven biology.
• Competitive compensation with equity participation.
• 401(k) with a strong employer match.
• Health, dental, and vision insurance.
• Generous PTO, work-life balance, and professional development opportunities.