🛠 Tech Stack

💼 About This Role

You'll lead the design and implementation of ML models and scalable systems for 4D auto-labeling in autonomous robotics at Serve Robotics. Your work will enable faster, smarter autonomy development by leveraging every robot mile. You'll bridge data engineering, ML systems, and model deployment to power next-generation end-to-end autonomy models.

🎯 What You'll Do

• Design and implement scalable auto-labeling pipelines for multi-modal robot data.
• Develop data-centric workflows connecting auto-labels to training and evaluation pipelines.
• Lead self-training, weak supervision, and sim-to-real adaptation to reduce manual labeling.
• Collaborate with autonomy teams to align labeling infrastructure with model workflows.

📋 Requirements

• 5+ years of experience developing production ML systems.
• M.S. or Ph.D. in Computer Science, Machine Learning, Robotics, or equivalent.
• Strong background in deep learning (PyTorch/TensorFlow) and scalable ML system design.
• Hands-on experience with multi-modal sensor data (LiDAR, camera, IMU, odometry).

✨ Nice to Have

• Experience with transformer-based models and E2E self-driving architectures.
• Contributions to large-scale robotics or autonomous driving ML stacks.
• Background in self-supervised learning, active learning, or semi-automated labeling systems.

🎁 Benefits & Perks

• 💰 Competitive base salary and equity.
• 🏥 Comprehensive health benefits.
• 🚀 Opportunity to work on cutting-edge robotics.
• 🌍 Remote-friendly with Bay Area preference.
• 🧠 Collaborative and driven team.