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Nvidia Controls Engineer Jobs (NOW HIRING)

NVIDIA

Senior HPC and Quantum Systems Engineer

Westford, MA · On-site

$108K - $148K/yr

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than ... controls, and low-latency connectivity meet quantum hardware requirements. • Serve as a technical ...

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All JobsNvidia Controls Engineer Jobs

Nvidia Controls Engineer information

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$55K

$96.6K

$131K

How much do nvidia controls engineer jobs pay per year?

As of Jun 18, 2026, the average yearly pay for nvidia controls engineer in the United States is $96,574.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,500.00 and $108,000.00 per year, depending on experience, location, and employer.

What is the difference between Nvidia Controls Engineer vs Nvidia Hardware Engineer?

AspectNvidia Controls EngineerNvidia Hardware Engineer
Required CredentialsBachelor's in Engineering, Computer Science, or related field; experience with control systemsBachelor's or higher in Electrical Engineering, Computer Engineering, or related; knowledge of hardware design
Work EnvironmentDesigning and testing control algorithms, software development, simulationHardware design, testing, prototyping, and integration
Industry UsageAutomotive, robotics, industrial automationGPU, AI hardware, consumer electronics

While both roles require engineering backgrounds and involve working within Nvidia's tech ecosystem, Nvidia Controls Engineers focus on developing control software and algorithms, whereas Nvidia Hardware Engineers work on designing and testing physical hardware components. The roles complement each other in product development but differ in their core responsibilities and skill sets.

What are some typical projects a Controls Engineer at Nvidia might work on, and how do these projects integrate with other engineering teams?

As a Controls Engineer at Nvidia, you can expect to work on projects involving the design, implementation, and optimization of automation and control systems for advanced manufacturing or testing equipment. These projects often require close collaboration with hardware, software, and robotics teams to ensure systems are integrated seamlessly and operate efficiently. You'll regularly participate in cross-functional meetings to align on requirements, troubleshoot issues, and improve system performance. This collaborative environment provides exposure to cutting-edge technology and offers opportunities to learn from experts in various engineering disciplines.

What are the key skills and qualifications needed to thrive as an Nvidia Controls Engineer, and why are they important?

To thrive as an Nvidia Controls Engineer, you need expertise in automation control systems, electrical engineering, and programming languages like Python or C++, typically supported by a relevant engineering degree. Familiarity with PLCs, SCADA systems, robotics platforms, and certifications such as Certified Automation Professional (CAP) are commonly required. Strong problem-solving skills, attention to detail, and effective communication help you excel in collaborative, high-stakes environments. These skills and qualifications ensure efficient system integration, innovation, and reliability in advanced manufacturing and automation projects.

What does an Nvidia Controls Engineer do?

An Nvidia Controls Engineer designs, develops, and implements control systems for hardware and software products, such as GPUs, autonomous machines, or robotics. They work on creating algorithms and integrating hardware to ensure optimal performance, safety, and efficiency of Nvidia's products. Controls Engineers at Nvidia collaborate with cross-functional teams, including hardware, software, and testing engineers, to deliver innovative solutions for automation and intelligent systems.
Infographic showing various Nvidia Controls Engineer job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $96,574 per year, or $46.4 per hour.
Senior Software Engineer - NIM Platform SDK and Framework

Senior Software Engineer - NIM Platform SDK and Framework

NVIDIA

Santa Clara, CA • On-site

$143K - $189K/yr

Full-time

Posted 17 days ago

Job description

Job Summary:
NVIDIA is the platform for every new AI-powered application, seeking a senior engineer to own and evolve the core NIM Platform SDK and microservice framework. This hands-on role involves solving deep software engineering challenges and collaborating across product teams to deliver production-grade software supporting NVIDIA and the wider AI ecosystem.
Responsibilities:
• Develop and advance the inference microservice framework: OpenAI-compatible API endpoints, inference backend integrations (vLLM, SGLang, TensorRT-LLM, Dynamo), middleware, observability instrumentation, and production hardening across cloud, on-prem, and Kubernetes environments.
• Architect significant new features in open-source codebases, shepherding them through project acceptance and into production.
• Build and optimize high-performance model download and caching pipelines across multiple cloud storage backends (NGC, HuggingFace, S3, GCS) - parallel transfers, integrity verification, and seamless multi-cloud operability.
• Implement the model profile and manifest system that ensures NIMs are optimized for every NVIDIA GPU platform - profile selection, validation, and multi-GPU configuration.
• Develop and refine cloud microservice patterns - service discovery, health checking, graceful degradation, API gateway integration, and end-to-end request lifecycle management - to ensure NIMs operate reliably at scale in diverse cloud deployment environments.
• Be a role model for high-quality code across Python, Rust, and C/C++, and model guidelines in test-driven development, agentic AI-assisted development, code review, and cross-team collaboration.
• Mentor teammates and establish high engineering standards for container quality, security, and operability.
Qualifications:
Required:
• BS or MS in Computer Science, Computer Engineering, or related field (or equivalent experience).
• 8+ years of demonstrated experience developing performant microservice, cloud software and/or platform infrastructure roles.
• Deep technical expertise in cloud-native microservice architecture, including service mesh, API gateways, load balancing, and distributed system build patterns.
• Expertise in high-performance data pipelines with parallel I/O, caching strategies, and integrity verification across distributed storage systems.
• Solid understanding of containerized application delivery using technologies such as Docker, Kubernetes, and Helm.
• Understanding of application security principles, including secure coding practices, vulnerability mitigation, secrets management, and supply chain integrity for containerized environments.
• Strong problem-solving skills grounded in first-principles reasoning and critical analysis.
• Excellent programming skills in Python and Rust, with strong foundations in algorithms, development patterns, and software engineering principles.
Preferred:
• Direct involvement in open-source inference backends such as vLLM, TRTLLM, or SGLang.
• Direct involvement in disaggregated serving frameworks like NVIDIA Dynamo.
• Experience building and operating production microservices at scale.
• Deep knowledge of multi-cloud deployment strategies across AWS, GCP, Azure, and OCI.
• Experience operating in regulated, air-gapped, or disconnected environments where strict security and compliance controls are required.
Company:
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. Founded in 1993, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.
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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing 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.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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