Software Engineer (E2E Autonomy)
Posted Updated
- Applied Intuition is pushing the frontier of autonomy and vehicle intelligence through next-generation AI Research
- In this role, you will enable this research effort by building ML tools, infrastructure, managing large datasets, and addressing challenges across the entire end-to-end (E2E) autonomy stack
- Join our research and production teams in creating the next generation of self-driving vehicles
- Here at Applied, we encourage all engineers to take ownership over technical and product decisions, closely interact with external and internal users to collect feedback, and contribute to a thoughtful, dynamic team culture
- Build tools and infrastructure to enable large-scale E2E autonomy research led by Dr. Wei Zhan
- 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
- Technologies: Python, Pytorch, CUDA, Bazel, Kubernetes, Spark, Flyte
- Strong fundamental skills in software & module design: can tame chaos with libraries & abstractions
- Rapid analytical and problem-solving skills
- Exceptional software generalist experience with ambition to contribute up and down the ML stack, onboard the vehicle, and in the cloud
- Bachelors, Masters or PhD degree in any field, or equivalent combination of education and work experience
- 3+ years of experience in any field, or equivalent combination of education and experience
- Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles
- Strong multi-language build system knowledge
- ML infra fluency - has used and/or contributed to ML and large data systems
- Distributed systems/compute (e.g. k8s, cloud-managed services at scale)