Discrete Planning Engineer (R6036)
- Pay
- $135,000 – $350,000 per year
- Location
- San Diego, CA · On-site
- Job type
- Full-time
- Level
- Senior
- Experience
- 4+ years
- Education
- Master's degree
- Listed
- 33 days ago
Skills & highlights for this role
- Mixed Integer Linear Programming
- Constraint Programming
- Convex Optimization
- Multi-Objective Optimization
- Gurobi
- Google OR-Tools
- CPLEX
- C++
- gdb
- Multi-threaded software debugging
Also useful
- Published research in optimization
- Motion planning
- Multi-agent autonomous systems
- Hardware-in-the-loop simulation
- Software-in-the-loop simulation
About the role
The Discrete Planning Group is a part of the Autonomy Team for Hivemind Enterprise Product. The group is an agile set of engineers focused on researching and developing state-of-the-art algorithms that drive intelligent and confidence-inspiring flight behaviors while accounting for an uncertain and dynamic world.
As a member of the group, you will work at the intersection of artificial intelligence, discrete optimization, and motion planning. You will architect and write high-quality software for core systems, set standards for software engineering, refine technical requirements, drive strategic technical improvements, and mentor other engineers.
What you'll do
- Research, design, and implement state-of-the-art algorithms for optimal task allocation, scheduling and temporal sequencing of heterogeneous teams of autonomous vehicles (land, air, other).
- Solidify and improve existing C++ based mission planning software applicable across disparate vehicle types and compute platforms.
- Work with our engineers, program managers, and product managers to define a technical roadmap for future autonomy solutions and SDK offerings.
Projects you might work on
- Breakdown a mission into assignable tasks based on agent capabilities such as navigating in contested and denied environments and adapting to mission changes in real-time.
- Construct feasible and optimal action plans for distributed teams of autonomous vehicles that also minimize human operator workload.
- Full software and hardware-in-the-loop simulation of complex multi-agent missions.
Required qualifications
- Typically requires a PhD with graduate work in Optimization or Operations Research. Master's degree with 4 or more years of work in the same areas.
- Expert in Integer or Mixed Integer Linear Programming, Constraint Programming, Convex Optimization, Multi-Objective-Optimization and using established solvers such as Gurobi, Google-OR, CPLEX etc.
- Significant experience in implementing algorithms in C++ and using debuggers such as gdb to troubleshoot execution within a multi-threaded environment.
Ways to stand out
- Past publications on Optimization(google scholar profile).
- Engineer II- $135,000-$200,000
- Senior Engineer: $165,000-$250,000
- Staff Engineer: $200,000-$300,000
- Senior Staff Engineer: $230,000-$350,000
- #LI-KC3
- #LE
Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity
Temporary employee offer package
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
About Shield AI
Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide.
Equal opportunity and legal notices
Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.
From Shield AI's careers page, first listed on Rolev.ai on October 10, 2026. Rolev.ai is not the employer.
How Rolev.ai helps with this application
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Common questions
What is the salary for the Discrete Planning Engineer (R6036) role at Shield AI?
The Discrete Planning Engineer (R6036) posting at Shield AI states compensation of $135,000 – $350,000 per year. It is listed as a full-time position. Final pay may depend on location, experience, and interview evaluation on Shield AI's official career site.
Where is the Discrete Planning Engineer (R6036) job at Shield AI located?
This Discrete Planning Engineer (R6036) position at Shield AI is located in San Diego, CA (On-site). Always check Shield AI's application page for specific state eligibility or relocation policies.
What qualifications are required for Discrete Planning Engineer (R6036) at Shield AI?
For the Discrete Planning Engineer (R6036) role, Shield AI highlights 4+ years of relevant experience; a master's degree; experience with Mixed Integer Linear Programming, Constraint Programming, Convex Optimization, Multi-Objective Optimization, Gurobi, Google OR-Tools. Rolev.ai can score your existing resume against these requirements and show any skill gaps before you apply.
How do I apply for the Discrete Planning Engineer (R6036) position at Shield AI?
This listing links directly to Shield AI's Lever application page. You can apply directly on Shield AI's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the Lever application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.