Bring promising AI research into autonomous systems that operate in the real world. Shield AI’s Perception team is looking for an engineer who enjoys exploring new ideas and making them work on real hardware. You’ll help turn advances in multimodal computer vision, visual foundation models, and embodied AI into useful capabilities for autonomous aircraft and vehicles.
Working alongside researchers and autonomy engineers, you’ll evaluate promising approaches, build prototypes, and carry successful ideas into the Hivemind product. You’ll combine learned methods with established perception techniques, working through the sensor, software, and compute challenges that make edge robotics different from a benchmark.
What you'll do:
- Evaluate emerging models and methods against representative sensor data and autonomy needs.
- Build prototypes and experiments that reveal strengths, limitations, and practical deployment opportunities.
- Combine learned and classical approaches to improve detection, tracking, geometric vision, or sensor fusion.
- Optimize and integrate capabilities for edge deployment, contributing Python and C++ software with support from experienced product engineers.
- Help deliver tested, documented capabilities and stay involved as other teams adopt them.
Required qualifications:
- A PhD in computer vision, machine learning (ML/DL), robotics, or a related field, or an equivalent record of advanced research and hands-on engineering.
- Research depth in an area such as multimodal vision, visual foundation models, video understanding, open-vocabulary perception, or embodied learning.
- Strong Python skills and experience with PyTorch or a comparable ML framework.
- A thoughtful approach to experiments, evaluation data, and understanding why models fail.
- Experience building substantial research software, an interest in developing production-quality C++, and a collaborative approach to solving problems.
Preferred qualifications:
- Experience bringing a research prototype into sustained use.
- Experience with robotics, real sensors, temporal data, or multi-sensor perception.
- Familiarity with vision-language models, vision-language-action models, or embodied AI.
- Experience with C++, edge inference, or model optimization using tools such as ONNX, TensorRT, or CUDA.
Similar Jobs at Shield AI
What you need to know about the San Francisco Tech Scene
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

