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Optimal Control Jobs in California (NOW HIRING)

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Optimal Control information

What is optimal control?

Optimal control is a branch of mathematics and engineering that focuses on finding a control policy for a dynamic system so that a specific objective, such as minimizing cost or maximizing performance, is achieved. It involves determining the best way to influence a system's behavior over time, typically through the use of differential equations and optimization techniques. Applications of optimal control can be found in areas like robotics, aerospace, economics, and process engineering.

What are some common challenges faced by professionals working in optimal control, and how can these be addressed?

Professionals in Optimal Control often encounter challenges such as handling complex, high-dimensional systems, ensuring solutions remain computationally feasible, and balancing accuracy with real-time performance requirements. Collaboration with multidisciplinary teams—including system engineers, software developers, and data scientists—is essential to develop effective models and algorithms. Staying updated with the latest optimization techniques and leveraging advanced computational tools can help address these challenges, and many organizations support ongoing training or conference participation for career growth.

What are the key skills and qualifications needed to thrive as an optimal control engineer, and why are they important?

To excel as an Optimal Control Engineer, you need a strong background in control theory, applied mathematics, and engineering, often supported by a relevant degree such as electrical, mechanical, or aerospace engineering. Proficiency with tools like MATLAB, Simulink, and programming languages such as Python or C++, as well as familiarity with optimization algorithms, is essential. Analytical thinking, problem-solving, and effective communication are key soft skills for translating complex models into practical solutions. These skills are vital for designing and implementing efficient control systems that optimize performance and stability in real-world applications.

What is the difference between Optimal Control vs Control Systems Engineer?

AspectOptimal ControlControl Systems Engineer
Required CredentialsDegree in Control Engineering, Applied Mathematics, or related fields; often requires knowledge of optimization and algorithmsDegree in Electrical, Mechanical, or Control Engineering; focuses on designing and implementing control systems
Work EnvironmentResearch, algorithm development, mathematical modeling, often in academia or R&DDesign, testing, and deployment of control systems in manufacturing, automation, or robotics
Industry UsageUsed in aerospace, robotics, finance, and advanced automation for optimal decision-makingApplied across industries for real-time control of machinery and processes

Optimal Control focuses on developing mathematical algorithms to determine the best control strategies, often involving complex optimization techniques. Control Systems Engineers implement and maintain these control strategies in practical systems. While both roles require a strong background in control theory, Optimal Control emphasizes theoretical and algorithmic development, whereas Control Systems Engineering centers on practical application and system integration.

What are popular job titles related to Optimal Control jobs in California?

For Optimal Control jobs in California, the most frequently searched job titles are:

What job categories do people searching Optimal Control jobs in California look for?

The top searched job categories for Optimal Control jobs in California are:

Infographic showing various Optimal Control job openings in California as of August 2026, with employment types broken down into 90% Full Time, and 10% Part Time. Highlights an 100% In-person job distribution.

Staff Software Engineer, Autonomy Capabilities - Space (R5368) with Security Clearance

Shield AI Inc

San Diego, CA • On-site

Other

Posted 12 days ago


Job description

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. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube . The Autonomy Capabilities Team develops functionality to automate single- and multi-agent teams of platforms in pursuit of mission objectives and acts as a central discipline-aligned focal-point for encouraging consistent usage of technical approaches across business portfolios. This team operates at all levels of the command-and-control hierarchy (from advanced control laws, through motion planning, and up to advanced tactical behaviors and multi-agent coordination) and across a multitude of mission sets, platform types, and operational domains (e.g., air, sea, space). The team puts a strong emphasis on both fundamentals (e.g., aircraft kinematics/dynamics, trajectory design, optimization, information fusion, efficient algorithms, etc.) and software integration skillsets (e.g. structures, protocols, threading, interface management, etc.) to bring market-differentiating capabilities to customers that seamlessly operate within their integration contexts. This position is perfect for an individual who enjoys solving complex problems across a diverse set of programs and integration contexts. An ideal candidate is expected to address operational system needs through a multitude of advanced methodologies that blend traditional control system approaches with advanced optimization. Developed solutions are expected to be integrated into real-world platforms with near-term program impacts and rewards and so balancing theory with practice and rigorous implementation is paramount. About the Job: Focusing on the space portfolio, you'll be creating autonomy capabilities for satellites and missile defense applications that span large-scale distributed optimization, automated tasking and scheduling, track fusion, RPO operations, and space vehicle motion/behavior planning. In many of these applications, you'll have the opportunity to build capabilities from the ground up and be the first to integrate them onto new platforms. You'll traditionally start with shorter-term R&D efforts or aligned customer programs but with the intent that successful efforts will grow into larger, multi-year programs. In many cases, the capabilities you will develop are at the cutting-edge and so demonstrating the ability to operate in grey space and at the intersection of the state-of-the-now and the state-of-the-possible is both exciting and crucial. As a Staff Engineer, you will lead the technical delivery of complex autonomy capabilities and demonstrate the ability to operate in significantly more grey space than more junior engineers, helping customers shape their requirements, define technical approaches for the team, and drive technical execution throughout the development process. You will combine your deep technical expertise with systems-level thinking to deliver scalable and operationally ready autonomy solutions. What You'll Do: * Multi-Objective Optimization - Use advanced optimization strategies to perform large-scale distributed decision making, task allocation, and resource scheduling in multi-satellite coordinated missions * Weapons Target Assignment - Employ cutting edge approaches for weapons target assignment and motion planning for fleets of space vehicles and interceptors that have critical roles in our national defense * Advance the State of the Art - Pioneer advanced topics in low-SWaP optimal control, tactical behavior management in cooperative and adversarial contexts, and information-aware planning * Rigorous Software Development - Develop high-performance software modules that are well-tested, have clear interfaces and span-of-control, and are ready for mid-to-high Technology Readiness Level (TRL) insertions * Cross-Functional Collaboration - Collaborate with cross-functional teams including perception, planning, simulation, hardware, and flight test to ensure seamless integration of autonomy solutions on real-world platforms * Deployment & Test Support - Deploy autonomy capabilities to real space vehicles, supporting analysis of mission logs to verify software performance and validate system operational effect * R&D and Road-mapping - Contribute to autonomy roadmaps by researching and prototyping new algorithms, identifying tactical capability gaps, and proposing novel solutions that advance Shield AI's mission * Travel Requirement - Members of this team typically travel around 10-15% of the year (to different office locations, customer sites, and flight integration events). Required Qualifications: * BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience * Typically requires a minimum of 7 years of related experience with a Bachelor's degree; or 6 years and a Master's degree; or 4 years with a PhD; or equivalent work experience * Proficiency in programming languages such as C++ and Python, and familiarity with real-time operating systems (RTOS) * Significant background in one or several robotic technology areas related to control systems, motion planning, optimization, tactical behaviors, and/or distributed decision-making * Significant experience with unmanned system technologies and accompanying algorithms (ideally in the space domain specifically) * Experience with simulation tools and environments (e.g., AFSIM, NGTS, or similar) for testing and validation * Strong problem-solving skills, with the ability to troubleshoot and optimize system performance * Excellent communication and teamwork skills, with the ability to work effectively in a collaborative, multidisciplinary environment * Ability to obtain a SECRET clearance or higher Preferred Qualifications: * Experience in multiple aerospace domains (e.g., air, land, sea, space) * Experience across a breadth of methodologies from classical control through optimization and applied ML/RL * Background in collaborative behaviors and swarm robotics * Familiarity with domain-relevant DoD or government programs * Hands-on experience supporting integration events, customer demos, and/or live exercises #LD #LI-ED1 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. ### 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.