lever
Lead Perception Engineer
Woven-by-toyota
Palo Alto, USA
Full-time
Senior · 5+ years experience
Hybrid
USD 161000-264500 yearly / year
Discovered 1 weeks ago
PythonC++
Free
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PythonC++
Key Skills for This Role
PythonC++
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- Driving the technical vision and multi-year strategy for World Understanding (including perception, mapping, fusion, on-board/off-board) software.
- Leading project execution, defining efficient engineering processes, and mitigating risks.
- Collaborate with cross-functional teams such as Data, Behavior (Planner/Controller/HMI), Developer Ecosystem, and Product Delivery while influencing technical decisions across the organization to drive innovation, ensure seamless system integration, and improve overall engineering efficiency.
- Develop state-of-the-art models to deliver desired driving environments in various sensor configurations.
- Increase speed of the component- and system-level model iteration while maintaining cost efficiency
- Incorporate data-driven approaches to improve system performance and unlock new capabilities for safety.
- Maintain the functional architecture design and lead review of technical designs
- Drive organizational metrics towards performance, safety, and quality
- Maintain external presence of the department through papers, patents, and presentations
- Assess and mitigate risk to the technical program
- Act in partnership with other Lead Engineers in AD/ADAS to solve high impact cross-functional issues
- Mentor and support engineers, fostering growth through code reviews, knowledge sharing, and collaboration with cross-functional teams to align technical solutions with business goals.
- Design reusable software components as part of an integrated system.
- Understand and fulfill the software practices that produce maintainable code, including simulation, continuous integration, code review, HIL testing, and in-vehicle testing.
- Build component and system level validation strategies that are leveraged to resolve complex interactions between components, increase performance, and evaluate design tradeoffs related to data-driven practices
- 10+ years of professional experience with machine learning applications or applied science
- MS or PHD in Machine Learning, Mechanical, Electrical, Computer, Aerospace Engineering, or similar
- Deep expertise in ML algorithms, frameworks, data-driven methods, supervised/unsupervised learning, multi-modality, multi-tasks training, and temporal/sequential modeling, and deployment of ML models at scale.
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