MLOps Engineer

About Boltz

About the role

About you

Essentials:

• 5+ years of experience in industry
• Strong experience deploying and operating machine learning models in production environments.
• Proven ability to optimize training and inference workloads, including profiling performance, reducing memory and compute usage, and improving throughput and latency.
• Hands-on experience with distributed frameworks and tooling
• Hands-on experience with PyTorch and the scientific Python ecosystem.
• Strong understanding of MLOps best practices, including experiment tracking, model versioning, reproducibility, and CI/CD for ML systems.
• Strong software engineering fundamentals, with experience building reliable, well-tested, and maintainable ML infrastructure.
• Comfortable collaborating closely with ML researchers to translate research models into robust production services.

Nice to have:

• Exposure to computational biology or chemistry workflows and data formats.
• Background working with large-scale scientific or numerical workloads.
• Experience operating ML systems under real-world constraints such as cost, latency, and reliability.

What we offer

• Opportunity to drive outsized real-world impact by building tools that empower thousands of scientists across the industry.
• Work alongside one of the most talent-dense teams in the field.
• Significant ownership and independence, with responsibility for driving projects from concept to deployment.
• Highly competitive salary with substantial equity ownership.