Boltz

Role Description As an MLOps Engineer, you will focus on optimizing, deploying, and operating large-scale machine learning models that power Boltz Lab. Your primary responsibility will be to ensure that advanced models for molecular modeling and design run efficiently, reliably, and cost-effectively across distributed systems. - Work closely with ML Researchers to turn trained models into production-ready services. - Optimize training and inference performance, reducing memory and compute overhead. - Scale workloads across multi-GPU and cloud environments. - Profile, improve model throughput and latency. - Harden systems for long-running and high-volume workloads. This role is ideal for someone who thrives on technical ownership and operational excellence, enjoys working close to systems and infrastructure, and is motivated by deploying high-impact machine learning systems at scale for real-world scientific use. Qualifications - 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. Requirements - 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. Benefits - 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.