Description
The Discrete Planning Group is part of the Autonomy Team for Hivemind Enterprise Product at Shield AI. As a Discrete Planning Engineer, you will work at the intersection of artificial intelligence, discrete optimization, and motion planning. Your responsibilities include:
- Researching, designing, and implementing state-of-the-art algorithms for optimal task allocation, scheduling, and temporal sequencing of heterogeneous teams of autonomous vehicles.
- Solidifying and improving existing C++ based mission planning software applicable across disparate vehicle types and compute platforms.
- Collaborating with engineers, program managers, and product managers to define a technical roadmap for future autonomy solutions and SDK offerings.
You might work on projects such as:
- Breaking down a mission into assignable tasks based on agent capabilities.
- Constructing feasible and optimal action plans for distributed teams of autonomous vehicles.
- Full software and hardware-in-the-loop simulation of complex multi-agent missions.
The role requires expertise in:
- Integer or Mixed Integer Linear Programming, Constraint Programming, Convex Optimization, and Multi-Objective Optimization.
- Using established solvers such as Gurobi, Google-OR, CPLEX, etc.
- Implementing algorithms in C++ and troubleshooting execution within a multi-threaded environment using debuggers like gdb.
A PhD in Optimization or Operations Research is typically required, or a Master's degree with 4 or more years of relevant work experience.
The salary compensation range is influenced by various factors, including skill set, level of experience, licenses and certifications, and specific work location.