1.12 Senior AI Software Engineer -- Edge Model Optimization & Deployment
23 days ago
Seattle
Job DescriptionField AI is 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.What You’ll Get To Do: • 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.What You Have:, • 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 PyTorch, C++, Python, and CUDA for AI/ML development and model optimization., • Hands-on experience with TensorRT, ONNX, TVM, or similar toolchains 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.The Extras That Set You Apart:, • Familiarity with JAX or additional ML frameworks beyond PyTorch., • Experience with compiler-level optimizations for GPU inference. We celebrate diversity and are committed to creating an inclusive environment for all employees. Candidates and employees are always evaluated based on merit, qualifications, and performance. We will never discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability, or any other legally protected status.