ML & Cloud Infrastructure Engineer
Gritt Robotics3 months ago
South San Francisco, CA, USAMid Level
Responsibilities
- Develop and deploy scalable AI training and validation pipelines in the cloud.
- Build distributed data ingestion, preprocessing, training, and evaluation pipelines.
- Deploy monitoring and CI/CD pipelines.
- Enable large-scale evaluation of AI models using cloud-based metrics.
- Support large-scale evaluation of autonomy software and models through cloud simulations.
- Optimize system performance, I/O, and GPU utilization.
- Build tooling and dashboards for experimentation, orchestration, and visualization.
- Integrate cloud tooling into workflows across teams.
- Take ownership of tasks with light supervision.
Requirements
- Degree in computer science or a related engineering discipline, or equivalent experience.
- 4+ years of experience deploying high-performance ML pipelines in production.
- Proficiency in Python and familiarity with C++ or Go.
- Experience with ML frameworks such as PyTorch.
- Experience with I/O and data-loading workflows and formats including Parquet, HDF5, and TFRecord.
- Experience deploying on cloud platforms such as AWS, GCP, or Azure.
- Experience with Docker, Kubernetes, and Airflow.
- Strong problem-solving skills.
- Legal authorization to work in the United States.
Benefits
- In-person role in the SF Bay Area.
- Opportunity to join an early team and have direct impact on product evolution.
- Work on robotics and AI systems deployed in challenging outdoor environments.
Tech Stack
Categories
Data EngineeringML Engineering