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Optimal Control Jobs in California (NOW HIRING)

PlusAI

Senior Research Engineer, Controls

Santa Clara, CA · On-site

$150K - $200K/yr

Develop tools and infrastructure for dataset generation, training, and evaluation to drive advancements in online control optimization * Ensure all model development keeps a real-time focus and ...

General Motors

Robotics Controls Engineer

Mountain View, CA · On-site

$138K - $211K/yr

About the Team The Local Planner Controller team builds optimization-based planning and control software for GM's Super Cruise system. The team formulates and solves online optimization problems that ...

General Motors

Robotics Controls Engineer

Mountain View, CA · On-site

$138K - $211K/yr

About the Team The Local Planner Controller team builds optimization-based planning and control software for GM's Super Cruise system. The team formulates and solves online optimization problems that ...

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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:

Optimal Control jobs near you
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.

Senior Research Engineer, Controls

PlusAI

Santa Clara, CA • On-site

$150K - $200K/yr

Full-time

Retirement

Re-posted 20 days ago

Job description

PlusAI is a Physical AI company pioneering AI-based virtual driver software for factory-built autonomous trucks. Headquartered in Silicon Valley with operations in the United States and Europe, Plus was named by Fast Company as one of the World's Most Innovative Companies. Partners including TRATON GROUP's Scania, MAN, and International brands, Hyundai Motor Company, Iveco Group, Bosch, and DSV are working with Plus to accelerate the deployment of next-generation autonomous trucks. If you're ready to make a huge impact and drive the future of autonomy, Plus is looking for talented individuals to join its fast-growing teams.
As a Research Engineer, you will deliver mission-critical improvements and new features for our autonomy motion planning and control stack. You will be a crucial part of our team, working alongside engineers, research scientists, and domain experts to build optimal and data driven controls to realize planned vehicle trajectories.
Your responsibilities will include the development of machine-learning vehicle models and learning based control policies leveraging the extensive data we collect every day across our autonomous trucking fleet. You will also have the opportunity to solve real-world autonomy system challenges by participating in vehicle performance analysis, tuning, and troubleshooting. You will contribute significantly to our commitment to pushing the frontiers of technological innovation in Autonomy.
Responsibilities:
  • Design, implement, and enhance control algorithms by developing frameworks that integrate MPC with learning based approaches (DL/RL/IL)
  • Work cross-functionally with domain experts to implement data driven controller design for scalability
  • Develop tools and infrastructure for dataset generation, training, and evaluation to drive advancements in online control optimization
  • Ensure all model development keeps a real-time focus and operates efficiently in compute-constrained environments
  • Take a lead role in the planning and execution of vehicle testing in the offline simulation environment and on the public road to systematically improve performance, as well as performing root cause analysis and debugging to address the issues
  • Track and incorporate the latest research advancements

Required Skills:
  • Master's or PhD degree in Computer Science, Mechanical Engineering, Robotics, Aerospace Engineering or related field
  • 2+ years of MLE experience or industry experience designing and developing for robotics applications
  • Strong foundation in motion control and modern neural network architectures, with expertise in at least one application area, such as IL/RL, time-series analysis, or dynamic system modeling
  • Skilled in debugging robotic systems within Linux environments, with strong programming expertise in Python and C++
  • Experience model development & training with modern frameworks (e.g. PyTorch)
  • Hands-on familiarity with data ingestion and processing pipelines

Preferred Skills:
  • Hands-on application skills in any of the following areas: adaptive and nonlinear control, MPC & optimal control, robust control, data-driven control, Kalman filters, etc.
  • Have a solid understanding of AV control, vehicle dynamics and drive-by-wire systems
  • Proven expertise with application, verification and validation for ADAS/autonomous driving features and functions

$150,000 - $200,000 a year
Your opportunities joining PlusAI
Work, learn and grow in a highly future-oriented, innovative and dynamic field.
Wide range of opportunities for personal and professional development.
Catered free lunch, unlimited snacks and beverages.
Highly competitive salary and benefits package, including 401(k) plan.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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