Über
Senior Machine Learning Engineer Location:
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 Opportunity This 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 Responsibilities Design and build end-to-end machine learning systems on large-scale real-world datasets Develop models in 3D computer vision and video understanding using spatial-temporal data Build and optimize human pose estimation and motion tracking systems Apply state-of-the-art ML techniques to ambiguous, evolving problem spaces Improve model performance, temporal consistency, and production scalability Partner with engineering, research, and product teams on system design and delivery Contribute to architecture decisions and ML best practices across the platform Requirements 3+ years of experience building and shipping machine learning systems Strong Python skills with PyTorch, TensorFlow, or similar frameworks Hands-on experience in at least one of the following: 3D computer vision Human pose / motion tracking Video understanding Solid understanding of ML workflows, evaluation, and production pipelines Comfortable operating in fast-moving, ambiguous environments Nice to Have MS or PhD in Computer Science, ML, or related field Experience with human kinematics, pose estimation, or motion capture (e.g., SMPL/SMPL-X) Familiarity with Transformers, CNNs, and multi-view geometry Experience with large-scale training or video-heavy ML systems Background in robotics, embodied AI, or egocentric perception Publications (CVPR, ICCV, NeurIPS, etc.) or strong open-source work
Sprachkenntnisse
- English
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