Posted 1w ago

Senior Engineer, Mathematical Optimization

@ Realtime Robotics
Boston, Massachusetts, United States
HybridFull Time
Responsibilities:solve problems, develop solvers, integrate solvers
Requirements Summary:Experience with numerical optimization methods; 2+ years with optimization libraries; strong software engineering; MS in a related field; in-office in Boston; strong English; team collaboration; startup environment; robotics experience a plus.
Technical Tools Mentioned:Google OR-Tools, CPLEX, Gurobi, Heuristic Solvers, C++, Linux
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Job Description

We're redefining how robots are deployed. Our platform enables users to simulate, test, and optimize entire robotic systems in parallel. By removing the barriers that have kept advanced robotics out of reach for all but the largest players, we're ushering in a new era of manufacturing—one where mass reshoring is not only viable, but inevitable.

With our industrial AI platform, we enable companies to design and optimize multi-robot workcells in the cloud, eliminating the need for manual robot programming. Our Resolver technology automatically generates collision-free robot programs by optimizing workcell layouts, task allocation, and robot paths, helping customers increase throughput and reduce the cost of industrial automation before deployment. 

We are searching for a motivated Optimization Engineer to improve the performance, reliability and capabilities of the optimization backend of our solution. This person will play a vital role on the team and help shape the future of industrial robotics.

Reporting to the Senior Director of Robotics, the Optimization Engineer will apply deep expertise in numerical optimization to support the robotics team and extend our core optimization capabilities.

In this position, you will:

  • Work with a team of robotics engineers to solve real-world automation problems using optimization and AI methods
  • Develop and maintain dedicated solvers for large-scale numerical optimization problems in robotics applications
  • Integrate state-of-the-art solvers for MIP, Constraint Programming, Scheduling into our product
  • Translate product requirements into constraints and optimization objectives
  • Improve and extend our optimization infrastructure and performance