Hybrid: Computational Biology MLOps Engineer for AI

Marlabs; United States; On-site; USD 140,000 - 190,000; Full time

Job summary

Marlabs, a global AI and Digital Solutions Consulting firm, seeks a Computational Biology MLOps Engineer to build and scale ML infrastructure for in silico protein design and engineering. You bridge cutting edge AI research and production systems at the intersection of machine learning, computational biology, and high performance computing.

You thrive in cross functional environments and partner closely with computational scientists and platform engineers to accelerate research velocity.

Qualifications

• 5+ years in software, DevOps, data engineering, or ML engineering with 3+ years in MLOps.
• Proven CI/CD expertise with GitHub Actions and IaC practices.
• Hands-on Kubernetes deployment and management for ML workloads.
• Experience with SLURM or similar HPC schedulers and distributed training optimization.
• Strong Python and ML framework knowledge (PyTorch/TF/JAX).
• Experience with ETL and scalable data pipelines; cloud exposure (AWS/GCP/Azure).
• Nice to have knowledge of protein data formats (PDB/mmCIF) and protein AI models.

Responsibilities

• Build and maintain ML infrastructure including CI/CD pipelines for training, evaluation, and deployment.
• Orchestrate compute across Kubernetes clusters and HPC environments for large-scale training.
• Develop scalable data pipelines delivering ML-ready datasets from biological sources.
• Create tools to support protein language models and diffusion-based approaches.
• Architect scalable systems across distributed environments handling multimodal data.
• Implement monitoring, logging, and cost-efficient production ML systems.

Skills

Software engineering

MLOps

CI/CD

Kubernetes

Python

ETL pipelines

Cloud platforms

Tools

GitHub Actions

SLURM

PyTorch

TensorFlow

JAX

Job description

Marlabs, a global AI and Digital Solutions Consulting firm, seeks a Computational Biology MLOps Engineer to build and scale ML infrastructure for in silico protein design and engineering. You bridge cutting edge AI research and production systems at the intersection of machine learning, computational biology, and high performance computing.

You thrive in cross functional environments and partner closely with computational scientists and platform engineers to accelerate research velocity.