Albert Invent
Staff ML Ops Engineer
Remote (United States) +1 · Remote · Staff · Full-time · Posted Feb 3, 2026
- Location
- Remote (United States)
Oakland, CA - Experience
- 7+ years of industry experience with a Bachelor's degree, or 5+ years with a Master's or PhD.
- Education
- Degree in Computer Science or a related field.
About the job
Build and operate Python backend services and cloud infrastructure that support production AI/ML workloads and scientific computing.
What you'll do
- Design and maintain Kubernetes infrastructure, backend APIs, and distributed systems for AI/ML workloads.
- Build data pipelines, storage integrations, and reliable systems for training and inference.
- Implement observability, CI/CD, infrastructure as code, and operational practices; collaborate with ML engineers to productionize research systems.
What they ask for
- Deep expertise in Python backend development and distributed systems; advanced Python skills including async programming and performance optimization.
- Strong Kubernetes and cloud infrastructure experience, including cluster management, networking, autoscaling, and troubleshooting.
- Experience supporting AI/ML teams or deploying ML systems in production, and experience with GPU workloads and scheduling.
- Production-scale software engineering experience; REST API, containerization, CI/CD, and infrastructure-as-code experience.
Nice to have
- Familiarity with scientific computing, chemistry, materials science, or data engineering tools such as Airflow or Dagster.
- Experience with vector databases, observability tools, message queues, open-source contributions, or mentoring engineers.
Tools
Python, Kubernetes, FastAPI, Flask, AWS, GCP, Azure, Terraform
AI focus
Build infrastructure and services for AI/ML workloads, including inference, agent-based workflows, and scientific computing pipelines that support materials discovery.
Model-written summary · the original posting is authoritative