Develop and deploy in-cabin computer vision ML modules for safety-critical perception. Design model architectures and training pipelines, build large-scale datasets from sensor inputs, validate and optimize models in real-world driving scenarios to improve fleet safety and efficiency.
Onsite in Foster City, CA | at least 3 days onsite
The Perception team is looking for a machine learning engineer to develop cutting-edge Computer Vision modules to enhance on-board perception of robots fleet, directly impacting safety and fleet efficiency. In this role, the ideal candidate will work on the full design and development cycle, including data collection, data set creation, machine learning models design and implementation.
Responsibilities:
- Design and develop in-cabin Computer Vision ML modules for safety critical perception and monitoring applications
- Implement Perception model architectures and sophisticated training techniques
- Build high quality datasets leveraging all the inputs from our sensor stack and the overall large scale data.
- Validate and optimize your solutions using real-world driving scenarios, directly contributing to the safety and reliability of our autonomous system
Requirements
Qualifications:
- Bachelor's Degree in Computer Science and/or Computer Engineering with 4+ years of experience
- Modern Computer Vision and Machine Learning background, specifically on 3D reconstruction, detection, classification, semantic segmentation
- Experience with training and deploying Deep Learning models
- Background in C++ and/or python
- Excellent communication skills
Bonus Qualifications:
Experience with any of the following:
- Self-driving industry experience
- Experience delivering ML model integration in latency-sensitive systems
- Experience with CUDA code
Benefits
- Health Care Plan (Medical, Dental & Vision)
- Life Insurance (Basic, Voluntary & AD&D)
- Paid Time Off (Vacation, Sick & Public Holidays)
- Training & Development
- Retirement Plan (401k, IRA)
Top Skills
3D Reconstruction
C++
Classification
Computer Vision
Cuda
Deep Learning
Detection
Python
Semantic Segmentation
Sigma Software Vertex San Jose, California, USA Office
San Jose 75E Santa Clara St, San Jose, California, United States, 95113
Similar Jobs
Cloud • Information Technology • Machine Learning
The Product Manager will define and deliver a scalable technology ecosystem for Data Center Operations, improve efficiency through data-driven solutions, and lead cross-functional collaboration to enhance product performance and operational excellence.
Top Skills:
AgileAIAnalyticsAPIsBmsCmmsData ModelsDcimJIRA
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Define and optimize next-generation DRAM system architectures, work with cross-functional teams, and engage with customers and executives to drive technology strategy.
Top Skills:
Dram SystemsMemory SystemsSilicon Architecture
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Develop signal integrity architectural strategies for high-speed interfaces, conduct feasibility analyses, create channel models, and translate insights into requirements.
Top Skills:
Electrical EngineeringHigh-Speed Interface DesignSignal Integrity ModelingSimulation
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine


.jpeg)