Skip to content
NEXTMOVEFDE careers · United States
Chef Robotics

Senior Perception Engineer

AI summary of the role

Senior Perception Engineer at Chef Robotics, owning the full perception stack for food-assembly robots: from camera integration and deep learning model training to real-time inference and field deployment.

What you’ll do

  • Design, train, and optimize deep learning models for detection, segmentation, pose estimation, and classification with focus on real-world robustness.
  • Build low-latency inference pipelines for real-time performance on embedded and edge hardware.
  • Develop multi-object tracking algorithms for reliable identification and motion prediction across frames.
  • Own end-to-end ML lifecycle: data collection, annotation, training, evaluation, deployment, and field debugging.

What you’ll bring

  • BS/MS/PhD in CS, Robotics, EE, or related field.
  • 5+ years combined research and industry experience in computer vision and ML, with production systems shipped.
  • Deep expertise in at least two of: instance/semantic segmentation, object detection, 3D perception, multi-object tracking.
  • Strong Python and production-quality code skills; hands-on PyTorch and full training pipeline.

Technologies

PyTorch · ROS · RGBD sensors · depth cameras · point cloud · multi-object tracking · instance segmentation · semantic segmentation · object detection · pose estimation · Isaac Sim · Gazebo

About Chef Robotics

AI-enabled robots that automate high-mix food assembly for manufacturers using adaptable manipulation software and a robotics-as-a-service deployment model.

Series A · 100–200 people

Source and classification

Production engineering · Evidence for this classification:

hardware, to training production-grade deep learning models, to ensuring those models perform accurately and efficiently in real-time on the factory floor. You will work on some of the most technically rich problems in applied robotics — dense instance segmentation of deformable food items, real-time inference under tight latency constraints, sensor fusion, and robust tracking in cluttered, dynamic environments. You will not just train models; you will design the pipelines that gather and curate data, define the architectures that balance accuracy and speed, and own the deployment and field troubleshooting of what you build. We are a small, high-ownership team. We work onsite five days a week and move with startup urgency — you will be expected to go deep technically while staying pragmatic about what ships. In this role, you will: Design, train, and optimize deep learning models
How jobs are selected

Employer postings · Data from · Sources