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Remote Nvidia Hardware Engineer Jobs in Michigan

Utilidata

AI Infrastructure Engineer

Ann Arbor, MI · On-site +1

$170K - $210K/yr

... fully remote candidates, with periodic travel expected for company retreats and key on-site ... Optimize GPU utilization and inference performance across our hardware fleet, including NVIDIA ...

Utilidata

Software Engineer, On Device

Ann Arbor, MI · On-site +1

$120K - $150K/yr

Utilidata is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically ... Collaborate with a cross-functional team of software, hardware, quality assurance (QA), and power ...

Utilidata

Principal Data Engineer

Ann Arbor, MI · On-site +1

$170K - $210K/yr

Utilidata is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically ... We're looking for a Principal Data Engineer to own the technical direction and execution of our ...

Utilidata

VP, AI & Applications

Ann Arbor, MI · On-site +1

$230K - $290K/yr

Utilidata is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically ... The VP partners with the VP, Engineering on the platform that runs these methods in production, and ...

Commerce Controls, Inc.

Project Engineer

Novi, MI · On-site +1

This position can be remote and or office within the Cleveland area. Requirements Equipment Design ... Instrument Calibration / Configuration, Hardware checkout, Software debug, Operator Ability to ...

Actalent

Infotainment Engineer

Ypsilanti, MI · Remote

... and remote services, ensuring high-quality, scalable, and secure solutions for North American ... At least 1 year of experience in infotainment system hardware and software design and/or validation.

Apply Early

Actalent

Connected Car Engineer

Ypsilanti, MI · Remote

... and remote services, ensuring high-quality, scalable, and secure solutions for North American ... At least 1 year of experience in infotainment system hardware and software design and/or validation.

Apply Early

Motorola

$95K - $105K/yr

Department Overview The Field Engineering team plays a crucial role in enhancing public safety by ... They handle all on-premise hardware and equipment installations for government and municipal ...

Gentex

Requirements Engineer II

Grand Rapids, MI · On-site +1

This role is not eligible for remote work. WHAT YOU'LL DO * Consistently execute the processes for ... coding). * electrical hardware development (microprocessors, power management). * digital ...

Gentex

Requirements Engineer II

Zeeland, MI · On-site +1

This role is not eligible for remote work. WHAT YOU'LL DO * Consistently execute the processes for ... coding). * electrical hardware development (microprocessors, power management). * digital ...

Thrive

Systems Engineer

Holland, MI · On-site +1

$45K - $55K/yr

Position Overview This role provides first-contact remote technical support for network, server ... hardware, printers, and peripherals * Basic networking knowledge, including TCP/IP, DNS, and DHCP

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All JobsRemote Nvidia Hardware Engineer JobsRemote Nvidia Hardware Engineer Jobs in Michigan

Remote Nvidia Hardware Engineer information

What does a Remote Nvidia Hardware Engineer do?

A Remote Nvidia Hardware Engineer focuses on designing, developing, and testing hardware components and systems for Nvidia products, such as graphics processing units (GPUs) and related technologies, while working from a remote location. They collaborate with cross-functional teams to ensure hardware solutions meet performance, reliability, and efficiency standards. Their work may include circuit design, board layout, hardware debugging, and supporting the integration of Nvidia hardware into various devices. Remote engineers use digital communication and collaboration tools to work effectively with global teams and contribute to innovative hardware solutions.

What is the difference between Remote Nvidia Hardware Engineer vs Remote Nvidia Software Engineer?

AspectRemote Nvidia Hardware EngineerRemote Nvidia Software Engineer
Required CredentialsBachelor's or higher in Electrical Engineering, Computer Engineering, or related; hardware design certificationsBachelor's or higher in Computer Science, Software Engineering, or related; programming certifications
Work EnvironmentDesigning and testing hardware components, collaborating with hardware teamsDeveloping software, drivers, and algorithms for Nvidia products
Industry UsageHardware development for GPUs, AI accelerators, and embedded systemsSoftware development for drivers, SDKs, and AI frameworks

The main difference is that Remote Nvidia Hardware Engineers focus on designing and testing physical hardware components, while Remote Nvidia Software Engineers develop the software that runs on Nvidia hardware. Both roles require technical expertise but differ in their focus areas within the Nvidia ecosystem.

What are some common challenges faced by Remote Nvidia Hardware Engineers, and how can they be addressed?

Remote Nvidia Hardware Engineers often encounter challenges related to effective collaboration and communication, especially when working on complex hardware design and testing with distributed teams. Staying aligned with project milestones, ensuring access to necessary hardware resources, and troubleshooting remotely can also be demanding. These challenges can be addressed by leveraging robust collaboration tools, maintaining clear documentation, and scheduling regular virtual meetings to synchronize efforts. Additionally, using remote desktop solutions and cloud-based simulation environments can help bridge the gap when physical access to hardware is limited.

What are the key skills and qualifications needed to thrive as a Remote Nvidia Hardware Engineer, and why are they important?

To thrive as a Remote Nvidia Hardware Engineer, you need a strong background in electrical or computer engineering, experience with GPU architecture, and proficiency in hardware design and validation. Expertise with tools such as Verilog/VHDL, simulation environments, and familiarity with Nvidia’s development platforms or relevant certifications is common. Strong problem-solving abilities, effective remote communication, and collaborative teamwork skills set top candidates apart. These competencies ensure efficient development, troubleshooting, and innovation in high-performance hardware solutions within distributed teams.
What are the most commonly searched types of Nvidia Hardware Engineer jobs in Michigan? The most popular types of Nvidia Hardware Engineer jobs in Michigan are:
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Remote Nvidia Hardware Engineer jobs near you
AI Infrastructure Engineer

AI Infrastructure Engineer

Utilidata

Ann Arbor, MI • On-site, Remote

$170K - $210K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 23 days ago

Job description

Utilidata is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically orchestrate power and unlock more compute capacity from existing energy infrastructure. For over a decade, we have applied AI to the electric grid - bringing real-time visibility and power-flow control to complex energy infrastructure. Our Karman platform, built on a custom NVIDIA module, brings that same capability to AI data centers, giving operators a way to better use the power already available to them.
The AI Infrastructure Engineer is responsible for designing, building, and owning the end-to-end infrastructure that serves Utilidata's AI and ML models across edge deployments, cloud environments, and data center integrations. They are also responsible for designing, building, and owning the integration of power data with AI inference software. This is Utilidata's first dedicated role of this kind, and will serve as the foundational function for how the company deploys and operates AI capabilities in production. The role requires deep technical expertise in ML model serving, distributed systems, and GPU infrastructure, with a strong emphasis on reliability, performance, and scalability. This position works cross-functionally with product, engineering, and data science teams and is open to fully remote candidates, with periodic travel expected for company retreats and key on-site engagements.
Responsibilities
  • Lead the design and build of Utilidata's AI inference platform - establishing architecture patterns, deployment standards, and operational practices that will scale with the company
  • Own end-to-end model serving infrastructure for Utilidata's AI infrastructure (on-prem and datacenter)
  • Build and maintain fault-tolerant, high-performance systems for serving AI models at scale, with a focus on low latency, reliability, and cost efficiency
  • Collaborate closely with algorithms engineers to integrate AI inference data and configuration with power optimization algorithms
  • Optimize GPU utilization and inference performance across our hardware fleet, including NVIDIA accelerators central to Utilidata's edge AI platform
  • Establish MLOps best practices including CI/CD pipelines for model deployment, monitoring, and rollback across environments
  • Contribute to infrastructure roadmap decisions, including build vs. buy tradeoffs, tooling selection, and platform evolution as the team grows

Minimum Qualifications
  • 5+ years of software engineering experience with a strong focus on AI infrastructure, backend systems, or distributed systems
  • Hands-on experience with AI model serving frameworks (e.g., vLLM, SGLang, Triton, TensorRT, TorchServe, or similar)
  • Understanding of container orchestration and cluster management (Kubernetes, Docker)
  • Experience deploying and operating infrastructure across both datacenter and on-prem environments
  • Strong knowledge of GPU workloads and the tradeoffs that come with them - you understand how inference differs from training, and why it matters
  • Proficiency in Python; C++, CUDA, Go, Rust a plus
  • Excellent communication skills and comfort working cross-functionally in a lean, fast-moving environment
  • Willingness to travel up to 10% of time

Enhanced Qualifications (Nice to Have)
  • Dynamo experience a plus
  • Experience with edge AI deployments or constrained compute environments
  • Familiarity with infrastructure as code (Terraform, Helm)
  • Experience with observability platforms (Datadog, Prometheus, Grafana)
  • Background in energy, utilities, or industrial IoT
  • Contributions to open-source ML infrastructure projects

Salary Range: $170,000 to $210,000 base compensation depending on experience plus stock options. Salary will be commensurate with an individual's skills, training, years of experience, and in line with internal compensation bands.
Location: This position can be performed remotely from anywhere in the United States.
Our Commitments:
Utilidata values the diversity of our team. We provide equal employment opportunities without regard to race, color, religion, creed, sex, gender, sexual orientation, gender identity or expression, national origin, age, physical disability, mental disability, medical condition, pregnancy or childbirth, sexual orientation, genetics, genetic information, marital status, or status as a covered veteran or any other basis protected by applicable federal, state and local laws.
We are committed to:
  • Creating a diverse and inclusive workplace that is welcoming, supportive, affirming and respectful
  • Empowering employees to solve problems and work together to make a difference
  • Providing mentorship and growth opportunities as part of a collaborative team
  • A flexible work environment with flexible paid time off
  • Competitive compensation and benefits, including health, dental, vision, and employer-match 401k

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