ML Engineer at Bucket Robotics

Bucket Robotics is hiring a Machine Learning Engineer to push the frontier of CAD-native computer vision for manufacturing. You’ll work on the core ML systems that turn 3D geometry and synthetic data into reliable, production-grade vision models deployed on factory floors. This role is perfect for someone who gets genuinely excited about new research ideas, enjoys deep analytical thinking, and wants to see those ideas survive contact with reality—edge deployment, distribution shift, weird lighting, and all. You’ll operate at the boundary between research and production: exploring new approaches, validating them rigorously, and shipping the ones that work. Design, train, and evaluate computer vision and ML models for inspection and perception Develop novel approaches for learning from CAD, synthetic data, and limited real-world data Run rigorous experiments to understand model behavior, failure modes, and tradeoffs Improve model robustness across lighting, materials, viewpoints, and manufacturing variation Optimize models for edge deployment (latency, memory, reliability) Collaborate closely with engineering to integrate models into production systems Build evaluation frameworks and

Details

equity range: 0.70% - 2.80%
experience: 3+ years
job type: Full-time
job url: https://www.ycombinator.com/companies/bucket-robotics/jobs/wamcLUR-ml-engineer
location: San Francisco, CA, US
role: Overview Bucket Robotics is hiring a Machine Learning Engineer to push the frontier of CAD-native computer vision for manufacturing. You’ll work on the core ML systems that turn 3D geometry and synthetic data into reliable, production-grade vision models deployed on factory floors. This role is perfect for someone who gets genuinely excited about new research ideas, enjoys deep analytical thinking, and wants to see those ideas survive contact with reality—edge deployment, distribution shift, weird lighting, and all. You’ll operate at the boundary between research and production: exploring new approaches, validating them rigorously, and shipping the ones that work. Responsibilities Design, train, and evaluate computer vision and ML models for inspection and perception Develop novel approaches for learning from CAD, synthetic data, and limited real-world data Run rigorous experiments to understand model behavior, failure modes, and tradeoffs Improve model robustness across lighting, materials, viewpoints, and manufacturing variation Optimize models for edge deployment (latency, memory, reliability) Collaborate closely with engineering to integrate models into production systems Build evaluation frameworks and metrics that reflect real-world manufacturing requirements Stay current with cutting-edge research and proactively test promising ideas Required Qualifications 3+ years experience developing ML systems in research or production environments Strong foundation in machine learning fundamentals and statistical reasoning Hands-on experience training deep learning models (e.g. PyTorch) Strong Python skills and comfort working in experimental codebases Enjoys deep problem-solving, experimentation, and analytical thinking Comfortable operating in ambiguity and iterating quickly Preferred Qualifications Experience in computer vision, 3D vision, or geometry-aware ML Familiarity with synthetic data generation, simulation, or domain randomization Experience deploying models

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Bucket Robotics