Lead Perception Engineer
- Lead perception ML model R&D by prototyping, validating, and iterating on existing and new model architectures, setting direction and best practices for the team.
 - Own end-to-end development of new ML models, from data strategy and initial development to optimization, production platform validation, and fine-tuning based on metrics and on-road performance.
 - Lead large, multi-person projects, shaping the overall Perception architecture and driving technical direction.
 - Mentor and enable other engineers through coaching, leading by example in writing high-quality code, conducting thorough code and design document reviews, and delivering rigorous ML experiment reports.
 - Drive agile development practices in a high-velocity environment, ensuring the team can adapt and deliver quickly.
 - Foster a collaborative, “get things done” mentality, promoting accountability and high performance across the team.
 - Collaborate with downstream stakeholders to define interfaces and requirements for the Perception stack.
 - Closely collaborate with Perception subteams to develop end-to-end solutions.
 
- MS, or higher degree, in CS/CE/EE, or equivalent in-industry experience.
 - 5+ years of experience with ML frameworks such as PyTorch, Caffee, Tensorflow.
 - Extensive experience with machine learning and classification.
 - 5+ years of experience in machine learning workflows: data sampling and curation, pre-processing, model training, ablation studies, evaluation, deployment, inference optimization.
 - Strong programming skills in Python or C++.
 - Passionate about self driving car technology and its potential for humanity.
 - Experience in writing production level code in a real-time operating system.
 - Strong communication skills and ability to communicate concepts clearly and precisely.
 
- Hands-on experience with building a perception stack for autonomous systems.
 - Experience in runtime optimization for runtime-critical systems on Linux and UNIX-like real-time operating systems.
 - Experience with CUDA or OpenCL.
 - Experience with automotive grade compute platforms.
 - Experience with building safety-critical software architectures.
 
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