Senior Robotics Manipulation Engineer

Dexterity

• $170K — $225K *
Consumer Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • BS/MS/PhD in Computer Science or a related discipline
  • 5+ years of relevant industry or research experience
  • Strong Python programming skills
  • Knowledge of Modern C++ and Linux
  • Experience with AI techniques including reinforcement learning and deep learning
  • Familiarity with distributed ML training platforms like Ray
  • Experience in task and motion planning

Responsibilities

  • Train models for robotic manipulation and control
  • Convert heuristic-based controls to learned models
  • Develop state space representations for robotic systems
  • Collaborate with cross-functional teams to optimize system solutions
  • Implement, test, and maintain high-quality software
  • Lead initiatives to enhance model rigor and performance

Benefits

  • Equity grants based on role and eligibility
  • Access to benefits and wellness resources
  • Total rewards philosophy recognizing contributions toward innovation
Full Job Description
As a Senior Robotics Manipulation Engineer, you will be working on a myriad of challenges related to manipulation, control, simulation and learning. You will bring a data driven approach to learned robot controls. You will also stay abreast of the latest progress in reinforcement learning, motion planning and controls, and other related fields in order to further develop Dexterity's technology foundations in physical AI.

Dexterity's robotic solutions integrate data from a multitude of sensors, including RGB cameras, depth sensors, force-torque sensors, encoders, system telemetry and human input. To better inform the planning and execution system, you may work on sensor fusion and state estimation techniques to leverage this multimodal sensory data.

You will work closely with the data platform, simulation, and robot operations teams to collect training data to improve your models.

In addition to core manipulation and controls, you will be responsible for building high quality, maintainable, and performant software. Ideally, you will possess strong software system and interface design skills.

Day to Day Activities:

  • Train models for robotic manipulation, force control, servoing etc.
  • Convert heuristics based control to learned models.
  • Develop the right state space representation for our Robotics Systems.
  • Collaborate with roboticist, machine learning engineers, mechanical engineers, and product managers to find optimal system solutions.
  • Implement, test, and maintain high quality software.
  • Lead efforts to improve the rigor and performance of models within Dexterity.


Required Skills:

  • BS/MS/PhD in Computer Science or a related discipline.
  • 5+ years of relevant Industry or Research experience.
  • Strong Python programming skills.
  • Knowledge of Modern C++ and Linux.
  • Experience with multiple of the following:
  • Artificial Intelligence (imitation learning, reinforcement learning, deep learning, LLMs)
  • Distributed ML Training Platforms (Ray or other)
  • Task and Motion Planning
  • Simulation


Nice to haves:

  • Experience with Git and modern CI pipelines.
  • Experience with Docker and Kubernetes
  • Previous startup experience


$170,000 - $225,000 a year

Our Total Rewards philosophy is designed to recognize contributions toward meaningful innovation. Base pay is one component of a broader compensation package that may include equity grants, benefits, and other incentives, depending on role and eligibility.

For this position, the expected base salary range is $170,000 to $225,000 annually. Actual compensation will be determined based on skills, experience, education, and market factors, and may vary accordingly.

Final compensation decisions are made individually and take a number of factors into consideration. Eligible employees may be considered for equity awards as part of their overall compensation. Access to benefits and wellness resources is provided in accordance with company policies and may vary based on role and location.

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