> Markdown version of [/jobs/ext/3057538-software-engineer-next-gen-compute](https://www.wearedevelopers.com/jobs/ext/3057538-software-engineer-next-gen-compute). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer, Next Gen Compute - **Company:** Motional Ad Llc - **Location:** Boston, MA, United States - **Experience:** Expert - **Salary:** $159,000.0 - $207,000.0 - **Contract:** Permanent contract - **Skills:** Nvidia CUDA, Linux, DevOps, Machine Learning, Programming Environments, Tensorflow, Software Engineering, System on a Chip, Graphics Processing Unit (GPU), High Performance Computing, Pytorch, Deep Learning, Information Technology, ONNX (Open Neural Network Exchange) Format, Machine Learning Operations, TensorRT - **Published:** September 24, 2026 - **Apply:** https://www.juju.com/job/16_abf0576c5 ## About the Role * Experience with machine learning accelerators, including GPUs, NPUs, TPUs, and their programming environments, including CUDA, TensorRT, or similar technologies. * Strong experience with modern C++ development in a Linux environment. * Experience with parallel and high-performance computing. * Comfortable with experimentation and evaluating different options as we work towards finding solutions that work. * A degree in Software Engineering, Computer Science, Electrical or Electronic Engineering, or similar technical field of study, or you have equivalent knowledge gained through your practical experience. Preferred, but not required: * Experience with PyTorch, TensorFlow, ONNX, and/or other ML frameworks. * Experience with embedded systems development for ARM-based system-on-chip architectures. * Experience working in a MLOps or DevOps environment. * Passion for self-driving technology and its potential for positive impact on the world. ## Description As a senior engineer in the Next-Gen Technologies team, you will help us improve the compute performance of our current generation and next-generation autonomous driving systems through participating in full lifecycle development from idea to proofs-of-concept to production. Specifically, you will: * Focus deeply on ML model deployment, integration of multiple ML models, and ML model optimization on embedded compute platforms. * Dive deep into the full ML software stack. Analyze ML workload performance on a variety of hardware processors, optimize ML models, improve ML software, and help us continually improve our stack through the application of efficient and effective ML approaches. * Design, develop, test, integrate, and optimize software and tools on a variety of ML compute architectures. * Collaborate with deep learning experts in perception, prediction, and other autonomous driving application areas to enable algorithms on GPU, NPU, and other ML accelerator architectures. * Optimize the utilization of GPU/NPU resources and sharing of GPU/NPU access across multiple programs running on the same system. * Lead designs to determine the needs of the system and how to best meet those needs through continually improving our ML software stack. * Advise peers and management on technical matters. ## Related Videos - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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