Staff ML Engineer, Foundation Models
- Lead the roadmap, research, development, and deployment of foundation models / VLAs / world models for our autonomy stack that will be applied to a variety of online and offline applications
- Discover new ways to leverage heterogeneous in-house data at Toyota scale
- Architect and implement scalable & efficient ML pipelines for training and fine-tuning large multi-modal, multi-task models
- Design experiments and benchmarks to evaluate foundation models for autonomy scenarios
- Optimize models for speed, accuracy, and robustness under diverse environmental conditions
- Translate cutting-edge research into useful production-ready solutions
- Enable and help other engineers on the team to be more effective through coaching and leading by example when it comes to writing high-quality code, providing high-quality code and design
- Work in a high-velocity environment and employ agile development practices
- Team player and “get things done” mentality
- Closely collaborate with internal and external teams to develop end-to-end solutions
- M.Sc. or higher degree in CS/CE/EE, or equivalent industry experience.
- 8+ years of experience with ML frameworks such as PyTorch or Tensorflow
- 6+ years of experience in machine learning workflows: data sampling and curation, pre-processing, model training, ablation studies, evaluation, deployment, inference optimization
- Prior proven experience in training and deploying state-of-the-art large foundation models leveraging large-scale data
- Strong programming skills in Python and C++
- Passionate about advancing self driving technology for the mass market
- Strong communication skills and ability to communicate concepts clearly and precisely
- Experience in production-level software development best practices.
- Hands on experience with building a perception stack for autonomous systems
- Experience in runtime optimization for Linux and UNIX-like real-time operating systems
- Experience with CUDA or OpenCL
- Experience with automotive grade edge-compute platforms and safety-critical software
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