Machine Learning Engineer

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This range is provided by Coco. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

$/yr - $/yr

At Coco
, our mission is to revolutionize urban logistics by empowering cities, boosting local economies, and delivering delightful customer experiences. We connect people with local merchants through our fleet of on-demand delivery robots, helping merchants reach their customers faster and more efficiently. By building innovative robotic systems that seamlessly navigate city sidewalks, Coco plays a key role in reshaping the future of last‑mile delivery and enhancing local businesses.

We are building an autonomy team to develop the AI technology that will enable our robot pilots to scale efficiently, sustainably, and safely. This involves building an autonomy stack from our millions of miles of last‑mile delivery routes, proprietary video streams, and LiDAR data. As a Machine Learning Engineer
, you will work with the CTO and the autonomy team to design, develop, and deploy machine learning models that power the autonomous vehicle’s perception, decision‑making, and control systems.

• Develop the architecture and implementation of machine learning models that power the autonomous vehicle’s perception, decision‑making, and control systems.
• Design and implement algorithms for object detection, sensor fusion, path planning, and real‑time decision‑making.
• Develop and maintain robust data pipelines to ingest, label, and preprocess data from multiple sensors (LiDAR, cameras, radar).
• Train and optimize deep learning models using simulation and real‑world data, focusing on system accuracy, robustness, and efficiency.
• Build simulation environments to test various driving scenarios and edge cases; work closely with the hardware team to ensure smooth integration.
• Ensure the autopilot system adheres to safety standards and regulations, incorporating redundancy and fail‑safe mechanisms.
• Play a key role in recruiting, mentoring, and leading a high‑performance machine learning and autonomy team.

• 2+ years experience in machine learning, computer vision, robotics, or autonomous systems.
• Proven track record of training and deploying a real world neural network.
• Expertise in the models and techniques currently used in autonomous driving or robotics systems in constrained production environments (e.g., SfM, SLAM, large‑scale mapping & localization, RL, imitation learning, neural rendering).
• Expertise in training and deploying deep learning models, particularly in vision (CNNs, object detection, semantic segmentation).
• Excellent programming skills in Python and C++; practical experience with PyTorch.
• Experience in optimizing large‑scale ML models and deploying them on distributed cloud/edge infrastructure.
• Strong leadership and communication skills.

• Contributions to open‑source autonomous vehicle frameworks (e.g., Autoware, Apollo).
• Experience with hardware integration and low‑level system programming (ROS, CAN bus).
• Familiarity with reinforcement learning and imitation learning for decision‑making in autonomous systems.
• Familiarity with regulatory and safety standards for autonomous vehicles (ISO 26262, UL 4600).

Compensation Range: $150K - $225K