Computational Biology MLOps Engineer

Job summary

Marlabs seeks a Computational Biology MLOps Engineer to build and scale ML infrastructure for in silico protein design and engineering, collaborating with computational scientists and platform engineers.

Qualifications

• 5+ years in software engineering, DevOps, data engineering, or ML engineering, including 3+ years in MLOps.
• CI/CD expertise with GitHub Actions and strong DevOps practices.
• Hands-on Kubernetes experience in managing containerized ML workloads.
• Proficiency with SLURM or similar job schedulers in HPC environments.
• Strong Python skills and experience with major ML frameworks.
• Experience building ETL processes and scalable data pipelines on cloud platforms.
• Preferred experience with scientific data and protein AI models.

Responsibilities

• Build and maintain ML infrastructure, including CI/CD pipelines for model training, evaluation, and deployment.
• Orchestrate compute across Kubernetes clusters and SLURM to optimize utilization for large scale training.
• Develop scalable data pipelines that deliver ML ready datasets from biological sources.
• Create tools for rapid iteration on protein language models and generative approaches.
• Architect systems that scale across distributed environments for multimodal datasets.
• Implement monitoring and alerting to ensure reliability and performance of production ML systems.

Skills

Relocation