Develop and research deep learning and vision algorithms for autonomous driving (detection, tracking, prediction, planning, SLAM). Lead end-to-end ML projects from data analysis through model evaluation, and collaborate across product, simulation, and algorithm teams to extend ML technologies into system components.
Company Introduction
Key ResponsibilitiesAt Bot Auto, we are revolutionizing the transportation of goods with our cutting-edge autonomous trucks, enhancing the quality of life for communities around the globe. With the agility of a start-up and the wisdom of seasoned experts, Bot Auto boasts a team that has achieved numerous world-firsts and unparalleled innovations. United by a shared vision, we create miracles and propel the future of transportation. Join us and transform your dreams into reality.
- Explore and propose new ideas using your knowledge and experience in deep learning, neural networks and large foundation models in autonomous driving including: end-to-end object detection, tracking and prediction, end-to-end planning and control, and end-to-end autonomous driving system, end-to-end online mapping. SLAM in localization and etc..
- Work on the entire life cycle of machine learning projects from data analysis, model experimentations to performance metrics verifications, and understand the entire workflow in great detail.
- Be exposed to many cross-team projects and collaborate with the product, simulation and other sibling autonomous driving algorithm teams to extend machine learning technology to all components.
- Have an advanced degree (Ph.D or Master’s) in related fields of study: computer science, computer engineering, robotics, mathematics, physics, and etc.
- Have in-depth knowledge and extensive experience in machine learning, and/or computer vision, modern transformer architecture, and employ SOTA techniques of machine learning.
- Be familiar with PyTorch, TensorFlow and other machine learning platforms and tools.
- Have strong motivation to work independently in a fast paced environment while collaborating with other teams on more complex and larger projects.
- Have a proven track record of research publications in top conferences and/or journals as the first author.
- Have knowledge and experience of generative models, model distillation, or model inference acceleration (e.g. TensorRT) techniques.
Similar Jobs
Artificial Intelligence • Information Technology • Machine Learning • Natural Language Processing • Productivity • Software • Generative AI
Build Superhuman Mail’s AI platform, including MCP tools, agentic workflows, personalization, LLM evaluation systems, and model-selection infrastructure. Partner across teams to provide reusable AI capabilities, ship production LLM features, and improve modeling approaches, data collection, and quality measurement. The role combines backend engineering with applied AI and requires adapting quickly as the field evolves.
Top Skills:
AnthropicAWSGoKubernetesLlmsMcpOpenaiPostgresPythonRedisTurbopufferTypescript
Cloud • Security • Software • Cybersecurity • Automation
Leads VP-level and senior executive searches across corporate functions, from strategy and market mapping through assessment, selection, negotiation, and closing. Advises C-suite stakeholders, develops talent strategies, engages passive executive candidates, manages confidential searches, and improves executive recruiting frameworks, assessment practices, reporting, and tools within a globally distributed Talent Acquisition team.
Top Skills:
AIDevsecopsGitlab
Artificial Intelligence • Fintech • Hardware • Information Technology • Sales • Software • Transportation
Manage business operations for the Services organization, including Implementation, Installation, and Customer Education. Optimize workflows, monitor performance, manage recurring business processes, produce Salesforce reports, and lead strategic projects that improve customer experience and team efficiency. Partner with Sales, Support, Product, and leadership on forecasting, territory alignment, QBRs, resource allocation, and operational decision-making in a high-growth SaaS environment.
Top Skills:
Ai-Driven ToolsSalesforceSFDCSpreadsheets
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



