Senior Staff Engineer, Autonomous Planning & Optimization

Shield AI; California (MO); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Equity

Bonus

Benefits

Job summary

Shield AI is seeking a highly experienced expert in optimization and autonomous systems to join the Discrete Planning Group. You will research, design, and implement state-of-the-art algorithms for task allocation, scheduling, and sequencing across heterogeneous autonomous vehicles, while enhancing C++-based mission planning software.

The role requires a PhD or a Masters with strong experience in optimization and operations research, with proficiency in ILP/CP/convex optimization and

Qualifications

• PhD with graduate work in Optimization or Operations Research.
• Masters degree with 4+ years of work in the same areas.
• Expert in Integer or Mixed Integer Linear Programming, Constraint Programming, Convex Optimization, Multi-Objective-Optimization and using solvers such as Gurobi, Google-OR, CPLEX.

Responsibilities

• Research, design, and implement state-of-the-art algorithms for optimal task allocation, scheduling and temporal sequencing of heterogeneous teams of autonomous vehicles.
• Solidify and improve existing C++ based mission planning software applicable across disparate vehicle types and compute platforms.
• Define a technical roadmap for future autonomy solutions and SDK offerings.

Skills

C++ development

Algorithm design

Optimization theory

Multithreaded debugging

Education

PhD in Optimization / Operations Research

Masters degree in related field

Tools

Gurobi

Google OR-Tools

CPLEX

Job description

Shield AI is seeking a highly experienced expert in optimization and autonomous systems to join the Discrete Planning Group. You will research, design, and implement state-of-the-art algorithms for task allocation, scheduling, and sequencing across heterogeneous autonomous vehicles, while enhancing C++-based mission planning software.

The role requires a PhD or a Masters with strong experience in optimization and operations research, with proficiency in ILP/CP/convex optimization and