Senior Machine Learning Engineer

Senior Machine Learning EngineerRole: Senior Machine Learning EngineerLocation: Santa Clara, CA (On-site, 5 days per week)I’m working with a well-funded, high-growth AI company building foundational infrastructure for robotics and embodied intelligence. The focus is on enabling next-generation foundation models through large-scale, real-world data systems.The team brings together experienced leaders across robotics, autonomous systems, and large-scale machine learning, and collaborates closely with leading AI labs and enterprise partners globally.The OpportunityThis is a Senior Machine Learning Engineer role focused on building scalable ML systems for real-world perception.You’ll work across the full ML lifecycle from data pipelines and model development through evaluation and production deployment, applying modern deep learning techniques to complex, multi-view, and temporal visual data.The work is highly hands-on and spans 3D computer vision, video understanding, and human motion tracking, with direct impact on embodied AI and robotics applications.Key ResponsibilitiesDesign and build end-to-end machine learning systems on large-scale real-world datasetsDevelop models in 3D computer vision and video understanding using spatial-temporal dataBuild and optimize human pose estimation and motion tracking systemsApply state-of-the-art ML techniques to ambiguous, evolving problem spacesImprove model performance, temporal consistency, and production scalabilityPartner with engineering, research, and product teams on system design and deliveryContribute to architecture decisions and ML best practices across the platformRequirements3+ years of experience building and shipping machine learning systemsStrong Python skills with PyTorch, TensorFlow, or similar frameworksHands-on experience in at least one of the following:3D computer visionHuman pose / motion trackingVideo understandingSolid understanding of ML workflows, evaluation, and production pipelinesComfortable operating in fast-moving, ambiguous environmentsNice to HaveMS or PhD in Computer Science, ML, or related fieldExperience with human kinematics, pose estimation, or motion capture (e.g., SMPL/SMPL-X)Familiarity with Transformers, CNNs, and multi-view geometryExperience with large-scale training or video-heavy ML systemsBackground in robotics, embodied AI, or egocentric perceptionPublications (CVPR, ICCV, NeurIPS, etc.) or strong open-source work