Applied Intuition is looking to solve the problem of accelerating the global adoption of safe, AI-driven machines by building tools and infrastructure to enable large-scale E2E autonomy research and productionizing next generation self-driving software
Requirements
- Python
- Pytorch
- CUDA
- Bazel
- Kubernetes
- Spark
- Flyte
- Strong fundamental skills in software & module design
- Rapid analytical and problem-solving skills
- Strong multi-language build system knowledge
- Distributed systems/compute (e.g. k8s, cloud-managed services at scale)
- ML infra fluency - has used and/or contributed to ML and large data systems
Responsibilities
- Build tools and infrastructure to enable large-scale E2E autonomy research
- Work directly with both AI research and engineering teams to productionize next generation self-driving software
- Help scale end-to-end training by identifying bottlenecks, especially as we continue to scale our GPU compute, onroad data volume, curation efforts, and eval systems
- Build ML tools, infrastructure, managing large datasets, and addressing challenges across the entire end-to-end (E2E) autonomy stack
- Contribute to a thoughtful, dynamic team culture
- Take ownership over technical and product decisions
- Closely interact with external and internal users to collect feedback
Other
- In-office work 5 days a week with occasional remote work
- Manage schedules responsibly
- Bachelor's, Master's, or Ph.D. degree (not explicitly mentioned but implied)
- Ability to work in a team environment
- Equal opportunity employer and federal contractor or subcontractor, abiding by regulations prohibiting discrimination
