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AI Robotic Grasping Strategy Developer

Riley Magnusson

Contract · Job · Los_Angeles

About the role

Picking a rigid box from a conveyor belt is robotics 101. Picking a transparent plastic bag of mixed vegetables from a cluttered bin without bruising anything — that's what our clients need, and it's one of the hardest manipulation problems in production robotics. Our grasping system must handle 500+ object types with varying shapes, materials, weights, and fragility levels. The current system uses a learned grasp planner that takes depth images and outputs gripper poses. It works well for rigid objects (94% success rate) but drops to 71% on deformable, transparent, and reflective items. You'll redesign the grasping strategy for these hard categories: incorporating tactile feedback, adaptive grip force control, and multi-attempt planning that learns from failed grasps in real time. This is a 10-month contract, 3 days per week in our Palo Alto lab with access to 8 robot cells equipped with force-torque sensors and tactile arrays. The robotics team is 12 engineers; you'll focus exclusively on grasping while others handle perception, motion planning, and system integration.

Responsibilities

  • Redesign grasping strategies for deformable, transparent, and reflective objects
  • Integrate tactile feedback into grasp planning and execution
  • Build adaptive grip force control for fragile item handling
  • Design multi-attempt planning that learns from failed grasps
  • Validate strategies against 500+ object types in lab testing
  • Document grasping recipes for different object categories

Requirements

  • 6+ years in robotics with hands-on manipulation experience
  • Deep expertise in grasp planning, force control, or tactile sensing
  • Strong reinforcement learning and PyTorch skills
  • Experience working with physical robot hardware
  • Track record of solving hard manipulation problems in production

Benefits

  • Hybrid — 3 days Palo Alto lab, remote flexible
  • Premium contract rate
  • Access to state-of-the-art robot cells and sensors
  • Work on unsolved manipulation problems
  • Potential conversion to permanent

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Categories

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch reinforcement learning computer vision docker

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Language

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AI Expertise

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch reinforcement learning computer vision docker

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