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Model Predictive Control Jobs in Nevada (NOW HIRING)

Sr AI/ML Engineer

Sparks, NV

$106K - $146K/yr

Design and prototype MPC-aligned models incorporating predictive modeling, optimization, and reinforcement-learning-based control. * Develop signal processing, perception, and planning pipelines ...

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Model Predictive Control information

What is Model Predictive Control?

Model Predictive Control (MPC) is an advanced method of process control that uses a mathematical model to predict and optimize the future behavior of a system. It works by solving an optimization problem at each control step to determine the best sequence of control actions, taking into account system constraints and objectives. MPC is widely used in industries such as chemical processing, energy, and automotive because it can handle multivariable control problems and anticipate future events. Its predictive nature allows for improved performance, stability, and efficiency compared to traditional control methods.

What is the difference between Model Predictive Control vs Control Systems Engineer?

AspectModel Predictive ControlControl Systems Engineer
CredentialsEngineering degree, control theory, process modelingEngineering degree, control systems, automation
Work EnvironmentIndustrial automation, process control, manufacturingDesign, develop, and maintain control systems across industries
Industry UsageProcess industries, chemical, oil & gas, manufacturingAutomation, robotics, embedded systems, industrial sectors

Model Predictive Control (MPC) focuses on advanced control algorithms for optimizing processes, while Control Systems Engineers design and implement various control systems. MPC is a specialized skill within control engineering, often requiring knowledge of process modeling and optimization, whereas Control Systems Engineers have broader responsibilities across multiple control technologies. Both roles are essential in industrial automation but differ in scope and application.

What are the typical challenges faced by engineers working with Model Predictive Control (MPC) systems in an industrial setting?

Engineers working with Model Predictive Control systems often encounter challenges related to model accuracy, computational demands, and real-time implementation. Ensuring the process model accurately represents the plant dynamics is critical, as discrepancies can lead to suboptimal control performance. Additionally, MPC algorithms can be computationally intensive, particularly for large-scale or fast processes, requiring careful tuning and optimization to maintain real-time operation. Collaboration with process engineers and IT specialists is common, as integrating MPC with existing control systems and plant infrastructure is a key part of the role.

What are the key skills and qualifications needed to thrive as a Model Predictive Control (MPC) Engineer, and why are they important?

To thrive as a Model Predictive Control Engineer, you need strong foundations in control theory, applied mathematics, and process engineering, usually supported by a degree in engineering or a related field. Proficiency with simulation tools such as MATLAB/Simulink, programming languages like Python or C++, and familiarity with industrial automation systems are typically required. Analytical thinking, problem-solving abilities, and effective communication skills help distinguish top performers in this role. These skills are essential for designing, implementing, and optimizing advanced control algorithms that improve system performance and reliability in complex industrial environments.
What are popular job titles related to Model Predictive Control jobs in Nevada? For Model Predictive Control jobs in Nevada, the most frequently searched job titles are:
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Infographic showing various Model Predictive Control job openings in Nevada as of July 2026, with employment types broken down into 95% Full Time, and 5% Contract. Highlights an 100% In-person job distribution.
Staff Motion Planning Engineer - Trajectory Generation

Staff Motion Planning Engineer - Trajectory Generation

Motional

Las Vegas, NV • On-site, Remote

Other

Posted 3 days ago

New


Job description

Mission Summary:

On our Motion team, you will serve as a technical leader, leveraging your deep expertise in motion planning, robotics, and software development to architect and advance the capabilities of production-ready autonomous vehicles. In this role, you will drive innovative research, own systemic design processes, and spearhead the implementation of performance-critical algorithms that enable safe, comfortable, and intuitive autonomous vehicle behaviors across Motional's fleet of robotaxis.

If you are passionate about autonomous driving, thrive on solving challenging motion planning problems, and are eager to make a significant impact in a rapidly evolving field, we want to hear from you.

Technical Scope:

  • Architect State-of-the-Art Solutions: Drive the long-term technical strategy and framework for motion planning and trajectory optimization algorithms to guarantee safe, smooth, and comfortable vehicle motion.
  • Scalable Core Software Architecture: Own the structural design of robust and scalable software that enables real on-road impact by evaluating, benchmarking, and integrating diverse optimal control techniques and motion planning algorithms. 
  • Systemic Code Quality & Governance: Establish code quality benchmarks and lead high-impact architectural code and design reviews (C++) based on an exhaustive understanding of the cross-functional teams' services and technologies. 
  • Advanced Engineering Infrastructure: Champion and define modern development toolchains, including next-generation testing frameworks, high-fidelity simulation, and continuous integration, to enable rapid development cycles across the organization. 

Role responsibilities:

  • Strategic Technical Leadership: Define, justify, and navigate complex system trade-offs and highly technical concepts to engineering peers and executive leadership to drive critical platform-level decisions. 
  • Cross-Functional Orchestration: Lead architectural co-design and alignment with adjacent teams working on decision/behavior planning, prediction, and vehicle control to build comprehensive, integrated, and safety-critical solutions. 
  • Subsystem Roadmapping: Author high-impact project proposals that anchor long-term technical roadmaps and span multiple safety-critical vehicle subsystems.
  • Engineering Mentorship: Cultivate the technical growth of senior and junior team members alike, fostering an organizational culture of product-focused engineering, rigorous research, and cutting-edge development. 

What we're looking for:

  • Extensive Production Experience: 5+ years (or equivalent expert level) of production-grade C++ software development, with a proven track record in real-time, low-latency, or safety-critical applications.
  • Educational Background: Bachelor's, Master's, or PhD degree preferred in Robotics, Computer Science, Computer Engineering, Electrical Engineering, or a related field.
  • Proven Technical Ownership: A distinct track record of defining, scaling, and leading large-scale technical development initiatives from initial problem formulation through algorithm design, validation, and on-vehicle production implementation.
  • Motion Planning & Control: Deep, domain-expert experience with Model Predictive Control (MPC), motion planning architectures, planning under uncertainty, vehicle dynamics/control, and closed-loop simulation environments.
  • Theoretical Excellence: Thorough, first-principles mathematical understanding of non-linear and numerical optimization algorithms (including interior point methods, sequential quadratic programming, and convex/non-convex optimization formulations).
  • Solver Optimization Expertise: Extensive experience deploying, customizing, and scaling numerical optimization solvers (e.g., IPOPT, Gurobi, OSQP, CasADi) within real-time embedded environments.
  • Strong knowledge of Python for simulation, data analysis, or rapid prototyping is considered a bonus


We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.