Physical AI Engineer (Robotics AD & Optimization)

ADVANCE YOUR CAREER. ADVANCE THE WORLD. At AMD, we believe technology can change lives for the better. It can heal us, entertain us, and make us more connected, productive, and understanding of the world around us. And we’re looking for talent who feel the same: people who want to leave the planet better than they found it, those who don’t shy away from humanity’s challenges but are determined to help solve them. AMD is powering the next generation of supercomputing, high-performance computing, cloud, and AI. Whether you’re designing next-gen processors, enabling AI breakthroughs, or creating go-to-market plans, every role at AMD contributes to something bigger — technology that moves the world forward. Main Responsibilities • Build and ship production AI models and training pipelines for robotics and autonomous systems. • Design, train, and scale large multimodal foundation models, including VLMs, world models, vision-language-action models (VLAs), 3D scene reconstruction (e.g., 3D Gaussian Splatting), perception systems, and data curation frameworks. • Develop and contribute to open-source codebases, tooling, and reference implementations to accelerate adoption and collaboration. • Advance the state of the art through publications and open model/code releases.Collaboration • AI Engineering Teams: Advance state-of-the-art perception and world models while building reusable training and evaluation pipelines. • Product and Software Engineering Teams: Co-design and integrate AI workloads into products; support CI/CD validation and provide actionable feedback on architecture and interfaces. • Internal and External Partners: Align technical roadmaps with academic, industrial, and internal stakeholders; translate objectives into practical plans and milestones. • Cross-Site Teams: Collaborate effectively with product and research teams across Europe and globally, ensuring clear ownership, strong feedback loops, and predictable delivery.Goals for the First 6 Months • Become proficient with the codebase, infrastructure, and end-to-end pipelines being developed for Physical AI applications. • Assess emerging developments in the field and translate insights into engineering priorities and a model roadmap. • Train and release an end-to-end model for a perception, world-model, or autonomous-systems use case, including training, evaluation, and deployment. • Lead client-facing implementation efforts to identify product needs and convert them into actionable technical deliverables.Ideal Candidate ProfileSkills and Qualifications • Master's degree, PhD, or equivalent experience in Machine Learning, Robotics, or a related field, including 3+ years of relevant industry experience. • Experience building robotics, perception, or autonomous systems pipelines. • Strong foundation in deep learning for perception and embodied decision-making, including transformers, diffusion models, and world models. • Hands-on experience with vision and multimodal foundation models (e.g., ViT, CLIP, DINO, LLaVA) and VLAs (e.g., OpenVLA, Pi-0.5). • Experience using simulation environments and RL/IL techniques to train and evaluate embodied agents (e.g., Isaac Lab, MuJoCo, Genesis, LeRobot). • Proficiency in Python and familiarity with C++ in production environments. • Strong experience with PyTorch; experience with JAX is a plus. • Strong engineering skills, including rapid prototyping, debugging, profiling, optimization, AI-assisted development tools (e.g., Claude Code, Cursor), and delivering maintainable production code.Preferred Qualifications • Experience building and operating large-scale machine learning systems, including training infrastructure and distributed computing environments. • Publication record in leading conferences such as CVPR, ICCV, ECCV, NeurIPS, ICRA, or IROS. • Experience profiling and optimizing GPU workloads using ROCm and/or CUDA. • Experience developing, maintaining, and supporting open-source software projects, including releases, documentation, and CI pipelines. • Experience with cloud platforms (AWS, GCP, Azure) and cluster orchestration technologies such as Slurm, Kubernetes, or Yarn. LocationSweden, Finland, Germany, Ireland, Poland, Spain or UK #LI-MH3 #LI-HYBRID Benefits offered are described: AMD benefits at a glance. AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process. AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here. This posting is for an existing vacancy. Main Responsibilities • Build and ship production AI models and training pipelines for robotics and autonomous systems. • Design, train, and scale large multimodal foundation models, including VLMs, world models, vision-language-action models (VLAs), 3D scene reconstruction (e.g., 3D Gaussian Splatting), perception systems, and data curation frameworks. • Develop and contribute to open-source codebases, tooling, and reference implementations to accelerate adoption and collaboration. • Advance the state of the art through publications and open model/code releases.Collaboration • AI Engineering Teams: Advance state-of-the-art perception and world models while building reusable training and evaluation pipelines. • Product and Software Engineering Teams: Co-design and integrate AI workloads into products; support CI/CD validation and provide actionable feedback on architecture and interfaces. • Internal and External Partners: Align technical roadmaps with academic, industrial, and internal stakeholders; translate objectives into practical plans and milestones. • Cross-Site Teams: Collaborate effectively with product and research teams across Europe and globally, ensuring clear ownership, strong feedback loops, and predictable delivery.Goals for the First 6 Months • Become proficient with the codebase, infrastructure, and end-to-end pipelines being developed for Physical AI applications. • Assess emerging developments in the field and translate insights into engineering priorities and a model roadmap. • Train and release an end-to-end model for a perception, world-model, or autonomous-systems use case, including training, evaluation, and deployment. • Lead client-facing implementation efforts to identify product needs and convert them into actionable technical deliverables.Ideal Candidate ProfileSkills and Qualifications • Master's degree, PhD, or equivalent experience in Machine Learning, Robotics, or a related field, including 3+ years of relevant industry experience. • Experience building robotics, perception, or autonomous systems pipelines. • Strong foundation in deep learning for perception and embodied decision-making, including transformers, diffusion models, and world models. • Hands-on experience with vision and multimodal foundation models (e.g., ViT, CLIP, DINO, LLaVA) and VLAs (e.g., OpenVLA, Pi-0.5). • Experience using simulation environments and RL/IL techniques to train and evaluate embodied agents (e.g., Isaac Lab, MuJoCo, Genesis, LeRobot). • Proficiency in Python and familiarity with C++ in production environments. • Strong experience with PyTorch; experience with JAX is a plus. • Strong engineering skills, including rapid prototyping, debugging, profiling, optimization, AI-assisted development tools (e.g., Claude Code, Cursor), and delivering maintainable production code.Preferred Qualifications • Experience building and operating large-scale machine learning systems, including training infrastructure and distributed computing environments. • Publication record in leading conferences such as CVPR, ICCV, ECCV, NeurIPS, ICRA, or IROS. • Experience profiling and optimizing GPU workloads using ROCm and/or CUDA. • Experience developing, maintaining, and supporting open-source software projects, including releases, documentation, and CI pipelines. • Experience with cloud platforms (AWS, GCP, Azure) and cluster orchestration technologies such as Slurm, Kubernetes, or Yarn. LocationSweden, Finland, Germany, Ireland, Poland, Spain or UK #LI-MH3 #LI-HYBRID Benefits offered are described: AMD benefits at a glance. AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process. AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here. This posting is for an existing vacancy.