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.
Skills Required
- PhD in computer vision, machine learning, robotics, or a related field, or equivalent advanced research and hands-on engineering experience
- Research depth in multimodal vision, visual foundation models, video understanding, open-vocabulary perception, embodied learning, or a related area
- Strong Python skills and experience with PyTorch or a comparable machine learning framework
- Experience designing experiments, evaluating data, and analyzing model failures
- Experience building substantial research software
- Interest in developing production-quality C++
- Collaborative approach to solving problems
- Experience transferring research prototypes 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 optimization using ONNX, TensorRT, or CUDA
What the Team is Saying
Shield AI Compensation & Benefits Highlights
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Healthcare Strength — Company materials highlight comprehensive medical, dental, and vision coverage with mental-health support and an EAP. Third-party benefits summaries also portray health coverage as a strong component of the package.
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Retirement Support — Offerings include a 401(k) with employer matching, cited on the careers page and independent benefits directories. Multiple sources indicate a match exists, though exact formulas have varied over time and warrant confirmation.
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Equity Value & Accessibility — Company communications describe equity for all full-time hires and stock benefits as part of total rewards. Independent listings also note company equity/RSUs as a standard element.
Shield AI Insights
What We Do
At Shield AI, you won't wait years to see your work reach the field. You'll build hardware and software that operates in the real world right now, in the hands of the people who depend on it. Hivemind, our AI pilot, has been flying since 2018. It has flown more than 30 platforms, including an F-16, and it now sits under a U.S. Air Force production contract for Collaborative Combat Aircraft. When you write code or shape a system here, you contribute to technology with a proven flight record and a clear production future. V-BAT flies intelligence, surveillance, and reconnaissance missions with an operational record that stretches from Ukraine to the Indo-Pacific. It delivers eyes where they matter most, in the most demanding conditions on earth. The teams behind it watch their work get tested where the stakes are real. X-BAT takes its first flight this year. It's an AI-piloted fighter that needs no runway, built to operate where traditional aircraft can't. Join now and you help shape a program at its earliest, most formative stage. That's the kind of ground-floor work that defines a career. Do the most impactful work of your life, on problems that matter. Autonomy at this level asks a lot of you. You'll take on problems in perception, planning, and control that few teams anywhere are equipped to solve. You'll work across disciplines, from aerospace and robotics to machine learning and systems engineering, alongside people who hold themselves to an exacting standard and expect the same from you. Our mission is clear: protect service members and civilians with intelligent systems. That purpose runs through every decision, every design review, and every deployment. It's why the work here carries a weight you can feel. Ready to join our mission? Explore our open roles and find where you fit.
Why Work With Us
Founded in 2015 by a former Navy SEAL, Shield AI builds AI pilots and uncrewed aircraft. Veterans aren't an afterthought here, they're at every level. It's why the work carries weight: AI pilots and uncrewed aircraft flying real missions, from Ukraine to the Indo-Pacific, protecting service members and civilians.
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Hybrid Workspace
Employees engage in a combination of remote and on-site work.
