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MACHINE LEARNING ENGINEER
- San Francisco, California, United States
- San Francisco, California, United States
Über
COMPENSATION $210K - $300K + 0.15% - 0.45% EQUITY
About the Role Training data quality is the bottleneck for physical AI. We are building ML systems that automatically process, validate, and enhance robotics datasets at massive scale. You will work on problems at the intersection of computer vision, robotics, and large‑scale ML infrastructure. Your work will directly impact how quickly the world's best robotics teams can train and deploy their models.
What You Will Do
Build ML pipelines for automated data quality assessment and filtering
Develop computer vision systems for pose estimation, object detection, and scene understanding
Create synthetic data generation pipelines to augment real‑world datasets
Optimize ML inference for real‑time processing of multi‑modal sensor data
Design evaluation frameworks to measure data quality and model performance
Collaborate with customers to understand their ML training requirements
What We Are Looking For
4+ years of experience in ML engineering or applied research
Strong background in computer vision (pose estimation, detection, segmentation)
Experience deploying ML models to production at scale
Proficiency in Python and PyTorch or TensorFlow
Familiarity with ML infrastructure (training pipelines, model serving, GPUs)
Strong software engineering fundamentals
Nice to Have
Experience with robotics, embodied AI, or imitation learning
Publications in top ML/CV venues
Experience with 3D vision or multi‑modal learning
Background in video understanding or temporal models
Benefits
Competitive salary at the top of market
Substantial equity grants with regular refresh
Comprehensive health, dental, and vision coverage
Unlimited PTO with genuine expectation to use it
Home office budget and top‑tier equipment
Weekly team dinners and quarterly offsites
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Sprachkenntnisse
- English
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