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Staff/Sr. Staff Machine Learning Engineer – Perception
| Company | Woven |
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| Location | Palo Alto, CA, USA |
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| Salary | $140000 – $264500 |
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| Type | Full-Time |
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| Degrees | Master’s |
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| Experience Level | Senior, Expert or higher |
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Requirements
- 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
Responsibilities
- Perception ML model R&D by prototyping, validating and iterating on existing and new model architectures.
- 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 large, multi-person projects and significantly influence the overall Perception 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.
- Team player and ‘get things done’ mentality
- 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.
Preferred Qualifications
- 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.
