Zipline
ML Infrastructure Engineer
$160K–$250K
South San Francisco, California, USA +1 · Full-time · Posted Sep 9, 2026
- Location
- South San Francisco, California, USA
South San Francisco, California, United States - Experience
- 3+ years of professional software engineering experience.
About the job
Build and scale data and machine-learning infrastructure that makes autonomy development faster, reproducible, observable, and safe.
What you'll do
- Build and operate infrastructure that lets learning algorithms use fleet data.
- Design and maintain systems for dataset creation and validation, training, evaluation, and deployment.
- Improve data pipelines and address bottlenecks in orchestration, performance, and reproducibility.
What they ask for
- Strong production software engineering practices in Python, including designing APIs, services, schemas, jobs, and operational workflows.
- Experience building reproducible data and machine-learning pipelines, and monitoring data, systems, pipeline failures, and model or evaluation signals.
- Working knowledge of ML concepts and experience with PyTorch or a similar ML framework.
- Experience with Kubernetes or another container orchestration system for production workloads; experience with cloud and on-premise production infrastructure.
Nice to have
- Experience in ML or data infrastructure, robotics, autonomy, aerospace, medical devices, or another safety-critical environment.
- Experience with AWS, Terraform or CloudFormation; deploying ML on hardware; large-scale training or dataset and model tooling; or annotation and active-learning workflows.
Pay
$160,000 - $250,000 USD starting cash range (target; not specified as base salary or total pay)
Tools
Python, PyTorch, Kubernetes, AWS, Terraform, CloudFormation
AI focus
Build infrastructure and pipelines for autonomy ML data, dataset management, distributed training, evaluation, and deployment.
Model-written summary · the original posting is authoritative