MLOps Engineer - Computational Biology & Protein AI

Marlabs; San Diego (CA); Hybrid; USD 140,000 - 180,000; Full time

Job summary

Marlabs is seeking a Computational Biology MLOps Engineer to join our team in San Diego, CA (onsite 3 days/week) or Indianapolis, IN. You will build and scale ML infrastructure supporting in silico protein design, bridging AI research with production systems across HPC environments.

You will collaborate with computational scientists and platform engineers, focusing on CI/CD, data pipelines, and cloud-based ML workloads.

Qualifications

• 5+ years in software, DevOps, data engineering, or ML engineering.
• 3+ years focused MLOps building production-grade ML infra.
• Proven CI/CD expertise with GitHub Actions and IaC.
• Hands-on Kubernetes deployment of ML workloads and HPC scheduling (SLURM).
• Strong Python and ML frameworks (PyTorch/TF/JAX).
• Experience with ETL, data pipelines, and cloud platforms (AWS/GCP/Azure).
• Familiarity with 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 to optimize heavy training loads.
• Develop scalable data pipelines delivering ML-ready datasets from biological sources.
• Create tools to enable rapid iteration on protein language models and diffusion approaches.
• Architect systems for distributed multimodal datasets and large foundational models.
• Implement monitoring, logging, and cost-efficient production ML systems.

Skills

CI/CD

Python

Kubernetes

DevOps

Data pipelines

Distributed training

ML frameworks

Cloud platforms

Protein language models

Multimodal data handling

Tools

GitHub Actions

SLURM

HPC environments

PyTorch

TensorFlow

JAX

Docker

AWS

GCP

Azure

Job description

Marlabs is seeking a Computational Biology MLOps Engineer to join our team in San Diego, CA (onsite 3 days/week) or Indianapolis, IN. You will build and scale ML infrastructure supporting in silico protein design, bridging AI research with production systems across HPC environments.

You will collaborate with computational scientists and platform engineers, focusing on CI/CD, data pipelines, and cloud-based ML workloads.