Staff Controls Engineer

Description

POSITION DESCRIPTION:

We are seeking a highly skilled Staff Controls Engineer specializing in Optimal Control with experience in renewable energy systems. The ideal candidate will have a strong background in control theory and advanced machine learning-based control techniques, including reinforcement learning and data-driven Model Predictive Control (MPC). The candidate will work on large-scale optimization problems related to the management and optimization of distributed renewable energy assets, Virtual Power Plants (VPPs), and energy storage systems.

Responsibilities

• Design and develop software solutions for optimal control and dispatch of renewable energy systems, including energy storage and distributed generation.
• Implement advanced control algorithms at scale, leveraging techniques such as reinforcement learning and data-driven MPC to optimize system performance.
• Develop models and simulations to predict and control the behavior of distributed energy resources under various grid conditions.
• Collaborate with cross-functional teams, including data scientists, hardware engineers, and energy market experts, to integrate advanced control strategies into real-time systems.
• Lead the development and deployment of machine learning models for energy system optimization in real-world applications.
• Optimize the performance of Virtual Power Plants (VPP) and battery dispatch in dynamic energy markets, ensuring system reliability and maximizing economic returns.
• Monitor, troubleshoot, and improve existing optimization software, ensuring scalability and robustness across large energy portfolios.
• Keep up-to-date with the latest advancements in control theory, machine learning, and renewable energy systems, and apply this knowledge to improve system performance.
  
  

Required Qualifications

• Education:Master’s or PhD in Control Engineering, Electrical Engineering, Computer Science, or a related field.
• Experience:Ph.D. with 3+ years OR Master’s with 5+ years of experience in software development with a focus on optimal control and system optimization in renewable energy.
• Technical Skills:
• Strong background in control theory and optimal control methodologies.
• Hands-on experience with advanced ML-based control techniques such as reinforcement learning and data-driven MPC.
• Proficient in programming languages such as Python, C++, or Java, with experience in implementing control algorithms at scale.
• Experience in cloud computing, distributed systems, and handling large datasets.
• Knowledge of renewable energy systems, including battery energy storage, distributed energy resources (DER), and grid integration.
• Familiarity with optimization algorithms, real-time control systems, and large-scale simulations.
• Understanding of energy markets and grid services is a plus.
• Soft Skills:
• Strong problem-solving skills and ability to work on complex, multidisciplinary challenges.
• Excellent communication skills and ability to collaborate effectively with cross-functional teams.
• Ability to work in a fast-paced, dynamic environment and manage multiple priorities.
  

Preferred Qualifications

• Experience with Virtual Power Plants (VPP) and renewable energy dispatch optimization.
• Familiarity with energy market operations, including demand response, frequency regulation, and energy arbitrage.
• Experience with cloud-native architecture and microservices for control applications.
• Experience with software development lifecycle tools, including version control (Git), CI/CD pipelines, and testing frameworks.
  
  

Hanwha Q CELLS America Inc. (“HQCA”) is a Qcells company, one of the world’s largest manufacturers and providers of solar photovoltaic (PV) products and solutions. Headquartered in Irvine, California, HQCA has been rapidly expanding its business in North America through the expansion of products and solutions, including distributed energy solutions, direct-to-homeowner solar sales and financing, and EPC services. We provide an opportunity to be part of an exciting and growing world-class global business in an interesting and expanding industry of the future.

The Distributed Energy (DE) team develops, invests in, and delivers distribution-connected solar and battery energy storage system (BESS) projects in North America. The DE team offers the full spectrum of BESS and PV+BESS solutions – from integrated ESS hardware and software, project development and investment to asset management and operations.

Physical, Mental & Environmental Demands

To comply with the Rehabilitation Act of 1973 the essential physical, mental and environmental requirements for this job are listed below. These are requirements normally expected to perform regular job duties. Incumbent must be able to successfully perform all of the functions of the job with or without reasonable accommodation.

Mobility

Standing

20% of time

Sitting

70% of time

Walking

10% of time

Strength

Pulling

up to 10 Pounds

Pushing

up to 10 Pounds

Carrying

up to 10 Pounds

Lifting

up to 10 Pounds

Dexterity(F = Frequently, O = Occasionally, N = Never)

Typing

F

Handling

F

Reaching

F

Agility(F = Frequently, O = Occasionally, N = Never)

Turning

F

Twisting

F

Bending

O

Crouching

O

Balancing

N

Climbing

N

Crawling

N

Kneeling

N

All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

The salary range is required by the California Pay Transparency Act and may differ depending on the location of those candidates hired nationwide. Actual compensation is influenced by a wide array of factors including but not limited to, skill set, education, licenses and certifications, essential job duties and requirements, and the necessary experience relative to the job’s minimum qualifications.

• This target salary range is for CA positions only and should not be interpreted as an offer of compensation.
  
  

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