Senior AI Software Engineer — Edge Model Optimization & Deployment

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Field AIis transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications.

Field AIis transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications.

• Design, implement, and optimize 2D/3D CNN and Transformer-based models for deployment on edge and embedded platforms (e.g., NVIDIA Jetson)
• Apply model compression techniques such as quantization, pruning, distillation, and weight sharing to achieve efficient real-time inference under strict constraints on power, bandwidth, and latency
• Convert, compile, and optimize neural networks for runtime using TensorRT, ONNX, CUDA, and C++
• Develop and maintain ROS nodes and interfaces that integrate perception models with the broader robotic system
• Collaborate closely with AI researchers, robotics engineers, and hardware teams to translate cutting-edge research into deployable solutions on edge devices
• Build benchmarks, profile and debug runtime issues, and validate performance against real-world scenarios
• Ensure the reliability, robustness, and stability of deployed models operating in challenging, resource-constrained environments

• 3+ years of professional experience in developing and deploying deep learning models for edge, embedded, or real-time systems
• BS, MS, PhD, or equivalent in Computer Science, Robotics, Electrical Engineering, or a related field
• Strong proficiency in Py Torch , C++, Python, and CUDA for AI/ML development and model optimization
• Hands-on experience with TensorRT, ONNX, TVM, or similar tool chains and compilers for edge deployment
• Proven track record applying model optimization techniques (quantization, pruning, distillation)
• Deep understanding of hardware limitations and performance tuning for Jetson, ARM, GPUs, or other embedded platforms
• Experience integrating AI models into ROS-based robotic systems
• Skilled in profiling and debugging GPU workloads, with familiarity using tools like Nsight or CUPTI
• Ability to work independently and collaboratively within cross-functional teams in a fast-paced, iterative environment

• Familiarity with JAX or additional ML frameworks beyond Py Torch
• Experience with compiler-level optimizations for GPU inference
• Background in deploying AI solutions for real-time robotics operating in the field

Compensation and Benefits

Our salary range is generous ($70,000 - $200,000 annual), but we take into consideration an individual's background and experience in determining final salary; base pay offered may vary considerably depending on geographic location, job-related knowledge, skills, and experience. Also, while we enjoy being together on-site, we are open to exploring a hybrid or remote option.

Why Join Field AI?

We are solving one of the world’s most complex challenges: deploying robots in unstructured, previously unknown environments. Our Field Foundational Models set a new standard in perception, planning, localization, and manipulation, ensuring our approach is explainable and safe for deployment.

You will have the opportunity to work with a world-class team that thrives on creativity, resilience, and bold…