Senior/Staff Online Mapping Machine Learning Engineer

5 days ago

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Woven by Toyota

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Mobility to Love, Safety to Live

software development • automated driving • vehicle software platform • smart city

1001 - 5000

Description

• Contribute to ML model R&D by prototyping, validating and iterating on existing and new model architectures towards an online mapping system. • Own development of new ML models end-to-end from data strategy, initial development, optimization, production platform validation, and fine tuning based on metrics and on road performance. • Lead multi-person projects and influence the overall AD/ADAS online mapping architecture and technical direction. • 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 document reviews and delivering rigorous reports from ML experiments. • Work in a high-velocity environment and employ agile development practices. • Collaborate closely with stakeholders in downstream customer teams to define interfaces and requirements for the Perception stack. • Closely collaborate with Perception subteams to develop end-to-end solutions.

Requirements

• MS, or higher degree, in CS/CE/EE, or equivalent industry experience. • 3+ years of experience with ML frameworks such as PyTorch, Caffee, Tensorflow • 3+ years of experience in machine learning workflows: data sampling and curation, pre-processing, model training, ablation studies, evaluation, deployment, inference optimization. • Extensive experience with machine learning and classification problems. • Strong programming skills in Python or C++. • Passionate about applying ML methodology to advance self driving technology. • Strong communication skills and ability to communicate concepts clearly and precisely. • Experience in production-level software development best practices. • Experience developing vision centric online mapping solutions. • Experience with commercially available automotive maps. • 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.