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    Job · 18510389

    SAN FRANCISCO · FULLTIME

    ML Engineer

    Bucket Robotics logo

    Bucket Robotics

    San Francisco · onsite · Posted 64d ago

    Sourced fromY Combinator
    $120K - $165K3+ yrsfulltimeSan Francisco

    About a minute. You'll make an account on the way through.

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    Section · 01

    About this role

    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 to edge or resource-constrained environments Background in robotics, manufacturing, or physical-world ML systems Authored technical reports, blog posts, or peer-reviewed research Previous startup or early-stage company experience What We Offer Competitive salary & meaningful equity – help define the core ML systems of the company Comprehensive benefits – health, dental, and vision insurance Professional development budget – conferences, courses, and research exploration A chance to work on hard problems – ML that has to work in the real world, not just benchmarks Our Values Innovation First : We push the boundaries of what's possible in ML and advanced manufacturing Ownership Mentality : We take responsibility and act like founders Collaborative Spirit : We work together to solve complex challenges Continuous Learning : We're always growing and improving Bucket Robotics is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

    Sourced from ycombinator

    Section · 02

    Skills

    CudaComputer VisionPytorchPythonDeep LearningMachine Learning

    Section · Company

    About Bucket Robotics

    Actively hiring
    Bucket Robotics logo

    Bucket Robotics

    Hiring

    Defect detection for manufacturing built from CAD and synthetic data.

    7

    employees

    2024

    2 years old

    San Francisco

    United States

    ₹1.2L – ₹1.6L PA

    This role

    About

    Bucket Robotics builds deployable computer vision systems for manufacturing — without labeling, long pilots, or fragile rules. We turn CAD and sample data into production-ready vision models that run on existing cameras and edge hardware. No manual labeling. No cold-start problem. Models deploy in minutes and adapt as parts, defects, and lines change. Our roots are in self-driving cars (Argo AI, Uber ATG, Stack AV), where we learned how to ship perception systems that operators trust in messy, real-world environments. We’re applying that playbook to factories: robust sensing, fast iteration, and tooling engineers actually enjoy using. Manufacturers struggle with inspection because parts are too variable for rules-based vision and too expensive to inspect by hand. Legacy systems are rigid, hardware-locked, and slow to customize. We take the opposite approach: software-first vision that fits into existing automation and scales across SKUs, facilities, and workflows. American Manufacturing is in the middle of a $700B automation push — but quality is still a trust problem. Bucket Robotics is building the vision infrastructure that lets factories automate inspection with confidence.

    Industries

    Machinery ManufacturingManufacturingRobotics

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