Senior Lead Algorithms Engineer - Robotics & Planning

Dexterity, Inc.; Redwood City (CA); On-site; USD 150,000 - 190,000; Full time

Benefits offered by this job

Comprehensive benefits

Equity

Job summary

Dexterity, Inc. in Redwood City, CA is hiring a Senior Lead Algorithms Engineer to tackle robot task and action planning using machine learning, optimization, and search techniques. You will engage with data platforms, physics simulation, and operations teams to improve the system’s world model and deploy solutions across warehouse automation.

You will drive high-quality software, model robotics systems, and push the boundaries of planning, control, and perception in real-world environments.

Qualifications

• Degree in Computer Science, Electrical Engineering, or Mathematics.
• 5+ years of relevant Industry or Research experience.
• Familiarity with Linux and git versioning.

Responsibilities

• Modify algorithms from modern optimal control to chess solvers.
• Collaborate with roboticists, ML engineers, mechanical engineers, and product managers to find optimal system solutions.
• Implement, test, and maintain high quality software.
• Develop and maintain accurate models of robotics systems.
• Integrate algorithms with existing software infrastructure, including development of any necessary auxiliary software.
• Deploy software to remote servers.
• Lead efforts to improve the rigor and performance of algorithms within Dexterity.

Skills

C++

Python

Linux

Git

5+ years experience

Experience: algorithms

Modern AI/ML

MCTS/DFS

Education

B.S. in Computer Science / Engineering or Math

Job description

Dexterity, Inc. in Redwood City, CA is hiring a Senior Lead Algorithms Engineer to tackle robot task and action planning using machine learning, optimization, and search techniques. You will engage with data platforms, physics simulation, and operations teams to improve the system’s world model and deploy solutions across warehouse automation.

You will drive high-quality software, model robotics systems, and push the boundaries of planning, control, and perception in real-world environments.