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Model Predictive Control Jobs in New York (NOW HIRING)

Reflex Robotics

Controls Engineer

New York, NY · On-site

$215K - $300K/yr

You have a good understanding of model predictive control, nonlinear optimization, sensor fusion strategies * You pride yourself on writing robust code that others can trust for years We primarily ...

Medal

World Model / Action Policy Researcher

New York, NY · On-site

$350K - $450K/yr

Experience with world models and predictive control - you understand how to train models that simulate dynamics and plan actions in learned environments. * Proficiency in reinforcement learning (RL ...

Thea Energy

Senior Control Systems Engineer

Kearny, NJ · On-site

$95K - $160K/yr

Work with the AI/ML and Plasma Control teams to integrate predictive control and digital twin ... Strong proficiency with EPICS or TANGO control frameworks, Simulink and MATLAB for system modeling ...

Thea Energy

Senior Control Systems Engineer

Kearny, NJ · On-site

$95K - $160K/yr

Work with the AI/ML and Plasma Control teams to integrate predictive control and digital twin ... Strong proficiency with EPICS or TANGO control frameworks, Simulink and MATLAB for system modeling ...

Gesture

Full Stack + AI Engineer

New York, NY

AI , Gesture's consumer intelligence engine - including data modeling, predictive algorithms, and ... Version Control: Git, GitHub Actions, Docker * CI/CD: Automated Docker pipelines via GitHub Actions ...

Gesture

Full Stack + AI Engineer (Remote)

New York, NY · Remote

$75K - $150K/yr

AI , Gesture's consumer intelligence engine - including data modeling, predictive algorithms, and ... Version Control: Git, GitHub Actions, Docker * CI/CD: Automated Docker pipelines via GitHub Actions ...

Gesture US, Inc

Full Stack + AI Engineer

New York, NY · On-site +1

$75K - $150K/yr

AI , Gesture's consumer intelligence engine - including data modeling, predictive algorithms, and ... Version Control: Git, GitHub Actions, Docker * CI/CD: Automated Docker pipelines via GitHub Actions ...

DTCC

Embedded Risk Director

Jersey City, NJ · On-site

DTCC offers a flexible/hybrid model of 3 days onsite and 2 days remote (onsite Tuesdays, Wednesdays ... to predictive risk management, enabling early identification of emerging risks and control ...

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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 New York? For Model Predictive Control jobs in New York, the most frequently searched job titles are:
What job categories do people searching Model Predictive Control jobs in New York look for? The top searched job categories for Model Predictive Control jobs in New York are:
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Model Predictive Control jobs near you

Controls Engineer

Reflex Robotics

New York, NY • On-site

$215K - $300K/yr

Full-time

Posted 7 days ago

Job description

Company Overview
Reflex Robotics is building affordable ($10k) wheeled humanoid robots to automate dangerous and repetitive tasks in manufacturing and logistics.
We envision a future where intelligent robots are doing all kinds of boring work that people hate doing-loading chicken nuggets into Costco boxes, lifting forty pound bags of dog food at Petco stores, and cleaning up cranberry juice spills in your apartment.
We are a three-year-old startup backed by Khosla Ventures, with $60M/year of revenue lined up pending successful pilots with e-commerce warehouses in 2025.
How Does It Work?
Our robots are designed and built entirely in-house by an engineering team that led development of the Stretch robot at Boston Dynamics and key systems on the Tesla Model S, X, and Y production lines. Reflex robots are high-performance, low-inertia, and optimized for low-cost manufacturing.
We've built the best real-time teleoperation system in the world, allowing a remote operator in South America to "play a video game" to control our robots at human-level speeds. This has allowed us to already ship robots with positive unit economics, and enables us to create a powerful human-intervention + RL product feedback loop.
Our system allows us to collect high-quality demonstrations at scale-giving us the proprietary data engine needed to train increasingly capable AI systems. We're on track to build the largest robotics dataset in the world, which will serve as an important long-term advantage.
Key Company Beliefs
  • High-quality, proprietary robotics data is the next foundation for generational AI companies (like Tesla FSD and ChatGPT).
  • Being nerd-sniped by maximizing an engineering metric is way less important than solving our customers' biggest pain points.
  • An insane work ethic is required for outsized success-and you'll be rewarded for it.

What We're Looking For
We are looking for controls engineers to join our team!
We're still a small team-which means high ownership, high equity, and the chance to shape the product from the ground up.
You should strongly consider applying if:
  • You've controlled the motion of real-world hardware before, not just in simulation-e.g., nanometer-scale control of EUV lithography machines, or making a quadruped do a backflip
  • You like to understand the entire system you're working with-e.g., you care about details like time-sync between two processors, or the stiffness properties of the mechanical assembly
  • You have a good understanding of model predictive control, nonlinear optimization, sensor fusion strategies
  • You pride yourself on writing robust code that others can trust for years

We primarily use C++, with some Python for prototyping. We don't use ROS.
You'd be joining a company that already has a solid core business-with working hardware, delighted customers, and profitable unit economics. Reflex is de-risked enough to see the hazy outlines of success, but still small enough that there's enormous upside up for grabs.
Compensation: $215,000-$300,000, depending on experience, skills, and qualifications
Come Join Us
This is a rare opportunity to help build a flagship robotics company from the ground up-and to do work that will truly matter, reshaping what people believe is possible in robotics.
We love to see the things you've worked on. Have a portfolio or insane project you've worked on? Share it. We're looking for people who push past the status quo, are passionate at work and in their own time-we're looking for people who want to win.

Apply