AI Factory Deployment Engineer
NVIDIA · Santa Clara, CA
- On site
- Full-time
- $184,000 / year
- Santa Clara, CA
This role may have been filled. Drop your résumé and we'll check if it's still open — or find you similar roles.
Job highlights
- Support AI Factory control system deployments.
- Collaborate on next-generation data center requirements.
- Adapt control system designs for AI Factory.
- Provide technical support for data center operations.
- Integrate IT to OT systems for advanced applications.
About the role
About NVIDIA
NVIDIA has been redefining computer graphics, PC gaming, and accelerated computing for 30 years. It’s an outstanding legacy of innovation that’s motivated by extraordinary technology—and outstanding people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, encouraging environment where everyone is inspired to do their best work. Come join our team and see how you can make a lasting impact on the world.About the Role
NVIDIA's AI Factories (e.g. data centers) host ground-breaking products across high-performance computing to machine learning applications for autonomous vehicles and healthcare. At the heart of our AI Factory is the ability to engineer mechanical and electrical designs in close coupling to NVIDIA's industry-leading GPU and DSX codesigns. We are seeking an AI Factory Controls and Monitoring Engineer to support control system deployments.What You’ll Be Doing
- Collaborate with product owners and technical leads to identify and collect requirements for our next-generation data centers.
- Support the global design standards for the data center controls and monitoring (DCCM) system, collaborating with internal teams to develop an execution strategy and life cycle management.
- Responsible for adapting control system reference designs and standards to AI Factory deployments. Key collaborator responsible for control system technical evaluation from site selection due diligence through site turnover to operations including: contractor selection, bid package development, MEP or equivalent experience and control system composition review, RFI response, submittal/as built reviews, and commissioning support.
- Provide technical support to DC operations controls engineers.
- Support IT to OT data integration enabling digital twins, agentic AI onboarding, coordinated leak detection and other applications.
- Support standardization in controls engineering quality approval, process control, product evaluation, vendor proposals, evaluate product reliability, automated testing and software.
- Collaborate with cross functional teams to make modifications to control settings and alarm thresholds to manage the data center space.
What We Need To See
- Excellent interpersonal and leadership skills critical for success, depending on building rapport and credibility with multiple stakeholders across the organization.
- BS in Engineering, CS or equivalent experience.
- 8+ years of experience with control system design, development and management on industrial or mission critical systems.
- Working knowledge of mechanical, electrical, life safety, and IT Networking systems associated with critical environments.
- Understanding of OPC-UA, and Modbus (TCP & RTU) protocols and how to integrate using these protocols.
- Troubleshooting, problem-solving skills and experience driving root cause analysis to complex projects under pressure.
- Experience with equipment commissioning, testing, or related activities.
- Experience with startup and configuration of Programmable Logic Controllers (PLCs) and SCADA workstations.
- Strong understanding of Sequence of Operations (SOO) for mechanical system control. Ability to create and iterate on SOOs.
Ways To Stand Out From The Crowd
- Experience with MQTT communication protocol, higher level data strategies, and integration to IT systems.
- Strong understanding of data center commissioning including Level 1 through Integrated Systems Testing.
- Strong understanding of document control and change control processes.
- Working knowledge and experience with Data Center Infrastructure Management (DCIM), EPMS systems, Ignition SCADA software development and deployment, and programming languages: Python, PHP, SQL.
- Working knowledge of data center power and cooling solutions, including advanced systems such as liquid cooling.
Key skills/competency
- AI Factory Deployment Engineer
- Controls Engineering
- Data Center Operations
- System Integration
- SCADA Systems
- PLC Programming
- IT/OT Integration
- Network Protocols
- Troubleshooting
- Commissioning
Skills & topics
- AI Factory Deployment Engineer
- Controls Engineering
- Data Center
- NVIDIA
- SCADA
- PLC
- IT/OT Integration
- System Design
- Commissioning
- High-Performance Computing
How to get hired
- Tailor your resume: Highlight experience in control systems, industrial environments, and specific protocols like OPC-UA and Modbus.
- Showcase leadership: Emphasize your interpersonal and leadership skills, detailing how you've built rapport with stakeholders.
- Demonstrate technical expertise: Detail your experience with PLCs, SCADA, commissioning, and IT/OT integration.
- Prepare for interviews: Be ready to discuss complex problem-solving, root cause analysis, and your understanding of data center infrastructure.
- Research NVIDIA: Understand their commitment to AI, data centers, and their innovative culture to align your answers.
Technical preparation
Master OPC-UA, Modbus, and MQTT protocols.,Practice PLC configuration and SCADA development.,Review data center mechanical/electrical systems.,Familiarize with Python, PHP, SQL programming.
Behavioral questions
Describe a complex system troubleshooting scenario.,How do you collaborate with cross-functional teams?,Give an example of building stakeholder credibility.,How do you manage multiple priorities under pressure?
Frequently asked questions
- What is the primary focus of the AI Factory Controls and Monitoring Engineer role at NVIDIA?
- The AI Factory Controls and Monitoring Engineer at NVIDIA is primarily responsible for supporting control system deployments within AI Factories (data centers), focusing on mechanical, electrical, and IT systems to ensure seamless operations and integration.
- What are the minimum educational requirements for the AI Factory Controls and Monitoring Engineer position?
- A Bachelor of Science in Engineering, Computer Science, or equivalent experience is required. While a degree is preferred, equivalent practical experience in control system design and management is also considered.
- What specific protocols does NVIDIA require knowledge of for this role?
- NVIDIA requires a working understanding of OPC-UA and Modbus (TCP & RTU) protocols, including how to integrate systems using them. Experience with MQTT is also a plus.
- How important are soft skills for the AI Factory Controls and Monitoring Engineer role at NVIDIA?
- Excellent interpersonal and leadership skills are critical for success. The role involves extensive collaboration, so the ability to build rapport and credibility with diverse stakeholders across the organization is essential.
- What kind of experience is expected regarding Programmable Logic Controllers (PLCs) and SCADA systems?
- Candidates are expected to have experience with the startup and configuration of Programmable Logic Controllers (PLCs) and SCADA workstations, demonstrating a practical understanding of these control systems.
- Does NVIDIA encourage candidates with data center commissioning experience to apply for this role?
- Yes, strong understanding of data center commissioning, from Level 1 through Integrated Systems Testing, is highly valued and will make a candidate stand out for this AI Factory Controls and Monitoring Engineer position.
- What programming languages are beneficial for an AI Factory Controls and Monitoring Engineer at NVIDIA?
- While not strictly required, knowledge of programming languages such as Python, PHP, and SQL is beneficial, particularly for those with experience in Data Center Infrastructure Management (DCIM) and SCADA software development.
- What is the typical career progression for an AI Factory Controls and Monitoring Engineer at NVIDIA?