Role: Software - ML & Cloud InfrastructureLocation: SF Bay Area (in-person)About the roleWe're looking for an experienced ML & Cloud Infrastructure Engineer to join our team. As an early member, you will play a pivotal role in architecting scalable cloud infrastructure for our AI and data pipelines. You'll need to thrive in a fast-paced startup environment where you'll wear multiple hats and have a direct impact on our product's evolution. Ideally, you have a proven track record of developing and deploying high-performance ML and cloud pipelines in production, and you're passionate about pushing the boundaries of what's possible in robotics with AI.
What you'll get to work on- Develop and deploy scalable AI training and validation pipelines in the cloud.
- Spin up distributed pipelines for data ingestion, pre-processing, training and evaluation.
- Deploy monitoring and CI/CD pipelines.
- Enable large-scale evaluation of AI models via cloud-based metrics.
- Enable large-scale evaluation of autonomy software and models via simulations in the cloud.
- Optimize performance, I/O and GPU utilization.
- Build tooling and dashboards for rapid experimentation, orchestration and visualization.
- Work with other teams to integrate cloud tooling into workflows.
What we look for- Degree in computer science or related engineering disciplines (or equivalent experience).
- 4+ years of experience deploying high-performance ML pipelines in production.
- Proficient in Python and comfortable with C++/Go.
- Experience with ML frameworks like PyTorch.
- Experience with IO and data-loading workflows, including formats like Parquet, HDF5, TFRecord etc.
- Experience with deploying on cloud platforms like AWS, GCP or Azure.
- Experience with tooling like Docker, Kubernetes, and Airflow.
- Should be comfortable taking ownership of tasks with light supervision.
- Must have excellent problem-solving skills.
- Legally authorized to work in the United States.
