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Remote Nvidia Engineering Jobs in Michigan (NOW HIRING)

Senior Software Engineer, DevOps

Ann Arbor, MI · On-site +1

$160K - $190K/yr

Utilidata is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically ... Bachelor's degree in Computer Science, Engineering, or a related field * Experience supporting or ...

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 ... Strong software engineering fundamentals, with the depth to evaluate code quality and set ...

Remote Nvidia Engineering information

What is a remote Nvidia engineer?

A Remote Nvidia Engineer is a professional who works for Nvidia, or with Nvidia technologies, from a location outside of a traditional office setting. These engineers may specialize in areas such as GPU development, AI research, software engineering, or hardware design, and they collaborate with teams virtually. Remote Nvidia Engineers use digital tools to communicate, manage projects, and contribute to cutting-edge technologies in graphics processing, artificial intelligence, and computing platforms. The remote aspect allows for flexible work arrangements and the ability to participate in global projects.

What are some common challenges faced by engineers working remotely for Nvidia, and how can they be overcome?

Remote engineers at Nvidia often encounter challenges related to communication across time zones, staying aligned with fast-paced project developments, and maintaining visibility within distributed teams. To overcome these, it's important to proactively engage in virtual meetings, leverage collaboration tools like Slack and Jira, and regularly update your team on progress. Building strong relationships with peers and seeking out mentorship opportunities can also help remote engineers stay connected and advance within the company.

What are the key skills and qualifications needed to thrive as a remote Nvidia engineer, and why are they important?

To excel as a Remote Nvidia Engineer, you typically need a strong background in computer engineering, programming (e.g., C++, Python), and experience with GPU architectures, often supported by a relevant degree. Familiarity with Nvidia tools like CUDA, cuDNN, and deep learning frameworks, as well as proficiency in remote collaboration platforms, are crucial. Strong problem-solving skills, self-motivation, and effective communication are vital soft skills for working independently and collaborating across distributed teams. These competencies ensure efficient development, troubleshooting, and innovation in Nvidia's complex, high-performance computing environments.

What is the difference between Remote Nvidia Engineering vs Remote Nvidia Data Scientist?

AspectRemote Nvidia EngineeringRemote Nvidia Data Scientist
Required CredentialsBachelor's in Engineering, Computer Science, or related field; experience with GPU programmingBachelor's or higher in Data Science, Statistics, or related; proficiency in machine learning and data analysis
Work EnvironmentDesign, develop, and optimize GPU hardware/software; collaborative teamsAnalyze large datasets, develop models, and generate insights; often cross-functional teams
Employer & Industry UsagePrimarily in hardware, AI, and high-performance computing sectorsPrimarily in AI, analytics, and research sectors

Remote Nvidia Engineering focuses on hardware and software development for GPUs, requiring engineering credentials and technical skills. Remote Nvidia Data Scientists analyze data and build models, requiring expertise in data science. Both roles are remote, but they serve different functions within Nvidia's ecosystem.

What are the most commonly searched types of Nvidia Engineering jobs in Michigan? The most popular types of Nvidia Engineering jobs in Michigan are:
What job categories do people searching Remote Nvidia Engineering jobs in Michigan look for? The top searched job categories for Remote Nvidia Engineering jobs in Michigan are:

Senior Software Engineer, DevOps

Utilidata

Ann Arbor, MI • On-site, Remote

$160K - $190K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 22 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.
We are seeking a Senior Software Engineer, DevOps to help design, build, and operate Utilidata's off-device platform that ingests, processes, and serves data flowing from edge AI devices. The role will build and maintain infrastructure across on-premises and cloud environments - bridging edge deployments with cloud-based data processing to support analytics, operations, and ML workloads at scale. This is a hands-on development role with deep technical ownership and cross-team visibility. This engineer will build and maintain the systems that keep our platform running, help shape infrastructure and deployment best practices, and support less experienced engineers. This engineer will partner closely with on-device and ML teams to ensure our off-device platform is resilient, well-instrumented, and ready to scale.
Responsibilities
  • Support the deployment and management of containerized applications using Kubernetes, ensuring optimal performance and availability
  • Contribute to strategic planning on how infrastructure solutions evolve to match Data Center partner requirements
  • Design, implement, and maintain scalable and reliable systems on AWS and/or on-premise
  • Utilize Terraform for infrastructure as code to automate the provisioning and management of cloud resources
  • Monitor system performance and uptime, ensuring systems meet established service level objectives (SLOs)
  • Support SOC2 security compliance requirements for data handling
  • Guide team members in DevOps practices, promoting a culture of reliability and excellence
  • Advocate for automation of operational tasks to enhance efficiency and reduce manual intervention
  • Collaborate with cross-functional teams to build and maintain CI/CD pipelines
  • Troubleshoot and resolve complex production issues, conducting root cause analysis and implementing corrective actions
  • Participate in on-call rotations and incident response teams
  • Assist in capacity planning, performance tuning, and technical decision-making
  • Drive continuous improvement initiatives for processes and infrastructure
Minimum Qualifications
  • 8+ years of development experience including experience in platform engineering, SRE, or distributed systems, with demonstrated senior-level impact
  • Experience designing and operating infrastructure across on-premises and cloud environments
  • Strong proficiency in container orchestration, particularly Kubernetes
  • Strong proficiency with AWS services and architecture
  • Hands-on experience with Terraform for infrastructure automation
  • Familiarity with monitoring tools (Prometheus, Grafana, or similar) and observability best practices
  • Strong problem-solving skills and attention to detail
  • Strong communication and collaboration skills, with experience contributing to technical outcomes
  • Willingness to travel up to 20% of time
Enhanced Qualifications (Nice to Have)
  • Bachelor's degree in Computer Science, Engineering, or a related field
  • Experience supporting or enabling MLOps platforms, model deployment pipelines, or ML-adjacent infrastructure
  • AI workload scheduling using Kubernetes
  • Knowledge of Apache Spark for large-scale data processing
  • Knowledge of database technologies (SQL, NoSQL)
  • Understanding of networking concepts and security best practices

Salary Range: $160,000 to $190,000 base compensation depending on experience and 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 is based at our company headquarters in Ann Arbor, Michigan, with flexibility for occasional remote work.
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