Controls Engineer Jobs

About The Position

Requirements

• PhD or equivalent experience in a relevant engineering or scientific discipline with emphasis on controls, dynamic systems, automation, machine learning, or intelligent systems; or equivalent R&D experience.
• Experience with agentic AI, LLM-based workflows, orchestration frameworks, or tool-using AI agents applied to scientific, industrial, or engineering use cases.
• Deep knowledge of control theory, including modern control, optimal control, Model Predictive Control (MPC), and system dynamics.
• Knowledge of robotics, mechatronics, high‑DoF systems, path planning, and dynamic modeling.
• Strong technical communication and collaboration skills.

Nice To Haves

• Ability to build data pipelines, workflows, and analytical tools for AI/ML tool chain which includes data cleaning, feature extraction, optimization, and insight generation.
• Strong programming skills in MATLAB, Python, C/C++, C#, Java, or similar languages.
• Create dashboards and use data visualization tools such as Python, or JavaScript Typescript frameworks.
• Ability to design, analyze, and troubleshoot control systems, sensors, actuators, pumps, VFDs, and automation hardware.
• Strong capability to read and interpret electrical schematics, mechanical drawings, P&IDs, flow charts, and cause‑and‑effect diagrams.

Responsibilities

• Develop and evaluate agentic AI systems that combine reasoning, tools, data, and simulation assets to enable advanced technical analysis, automation, and human-in-the-loop decision making.
• Integrate large language models (LLMs), retrieval-augmented systems, and AI agents with controls, modeling, and optimization frameworks.
• Develop machine learning, data analytics, and hybrid physics-AI approaches to improve system performance, automation, and operational efficiency.
• Develop software tools, workflows, orchestration pipelines, and visualization capabilities to support AI-enabled engineering and operations.
• Conduct research and development in advanced controls, robotics, dynamic modeling, and automation for complex engineering systems.
• Design & apply advanced control techniques including adaptive, nonlinear, robust, optimal, and model predictive control (MPC).
• Develop and validate dynamic models, simulations, and system identification methodologies.
• Collaborate with multidisciplinary teams across engineering, software, data science, and operations.
• Contribute to technical innovation through patents, publications, conferences, and internal programs.

Benefits

• Comprehensive and affordable benefits package that covers your physical, emotional, financial, and parental needs
• Wide range of programs designed to help you thrive at work and at home