Merge Labs
MLOps Research Engineer
$200K–$265K
San Francisco Bay Area · On-site · Full-time · Posted Aug 28, 2026
About the job
Build and own ML infrastructure that enables computational scientists to train, evaluate, deploy, and improve models for molecular discovery, biophysical modeling, signal processing, and computer vision.
What you'll do
- Build infrastructure for active learning and closed-loop optimization, including data ETL, ML modeling, and library design.
- Implement model registries, evaluation frameworks, automated reporting, CI/CD pipelines, and resource orchestration.
- Own the ML engineering roadmap, mentor computational scientists, and establish engineering best practices.
What they ask for
- Deep experience in ML infrastructure, systems engineering, and production ML workflows.
- Proficiency with Python, PyTorch, JAX, Ray, Kubernetes, and cloud services (AWS / GCP / Azure).
- Deep experience with experiment-tracking and model-management tools (MLflow, Weights & Biases).
- Strong software engineering fundamentals, including version control, modular design, CI/CD, and distributed computing.
Nice to have
- Familiarity with neuroscience.
- Experience bridging machine learning and experimental science, including work with sparse, noisy, or high-cost data.
Pay
$200K – $265K USD base salary
Tools
Python, PyTorch, JAX, Ray, Kubernetes, AWS, GCP, Azure
AI focus
Develop and support ML infrastructure and workflows for AI-enabled molecular discovery, biophysical modeling, signal processing, computer vision, and active-learning optimization.
Model-written summary · the original posting is authoritative