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Remote Reliability Engineer Jobs in Commerce, MI

Utilidata

AI Infrastructure Engineer

Ann Arbor, MI · Remote

$170K - $210K/yr

... 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 ...

ABB

Protection and Control Engineer

MI · Remote

While this is a full remote position, there is preference for candidates located in the Northern ... ABB's Service Division partners with our customers to improve the availability, reliability ...

Troutman Pepper

Senior Data Engineer

Detroit, MI · Remote

$104K - $142K/yr

Demonstrated ability to add value, build efficiency, and improve accuracy and reliability of ... Prior law firm or professional services experience beneficial. #LI-Remote The Firm will comply with ...

Utilidata

Principal Data Engineer

Ann Arbor, MI · On-site +1

$170K - $210K/yr

... reliability investments, and technical debt reduction in alignment with the broader platform ... Mentor and grow engineers with an emphasis on raising technical depth - delegate meaningful work ...

General Motors

Senior Mobile iOS Engineer

Warren, MI · On-site +1

$131K/yr

Hybrid/Remote/Onsite Hybrid: This role is categorized as hybrid. This means the successful ... reliability, and security requirements. * Build, test, and maintain high-quality, reusable, and ...

OneStream

AI Engineer

Birmingham, MI · Remote

... the reliability of releases. * Participate and eventually lead technical design sessions to ... OneStream is an Equal Opportunity Employer. #LI-REMOTE #LI-JP1

OneStream

AI Engineer

Birmingham, MI · Remote

... the reliability of releases. * Participate and eventually lead technical design sessions to ... OneStream is an Equal Opportunity Employer. #LI-REMOTE #LI-AS1

IT Labs

Senior DevOps Engineer

Detroit, MI · Remote

$133K - $170K/yr

... ensure platform reliability, security, and compliance. You will collaborate closely with ... Remote * US-based -- US citizenship is required * Contract or B2B arrangement Our values We are a ...

IT Labs

Lead DevOps Engineer

Detroit, MI · Remote

$54 - $74/hr

... s Engineer to support one of the most innovative companies in the digital health space. Our client ... Remote * Contract or B2B arrangement Our values We are a company that seeks the best for both our ...

Canopy

Senior Machine Learning Engineer

Detroit, MI · Remote

$126K - $180K/yr

As a Senior Machine Learning Engineer within the AI Squad at Canopy and reporting to the Director ... Proficiency in Unix-based environments (Linux, macOS) including working with remote servers and ...

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All JobsReliability Engineer JobsRemote Reliability Engineer JobsRemote Reliability Engineer Jobs in Commerce, MI

Remote Reliability Engineer information

See Commerce, MI salary details

$54.8K

$105.9K

$126.6K

How much do remote reliability engineer jobs pay per year?

As of Jul 14, 2026, the average yearly pay for remote reliability engineer in Commerce, MI is $105,892.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,000.00 and $115,800.00 per year, depending on experience, location, and employer.

What is the difference between Remote Reliability Engineer vs Remote Site Reliability Engineer?

AspectRemote Reliability EngineerRemote Site Reliability Engineer
CredentialsTypically requires certifications like AWS Certified Solutions Architect, Linux Foundation certificationsSimilar credentials, often with additional focus on site-specific tools and monitoring
Work EnvironmentPrimarily remote, focusing on cloud infrastructure and system reliabilityRemote with some on-site responsibilities, focusing on infrastructure and operational stability
Industry UsageUsed across tech, cloud providers, SaaS companiesCommon in data centers, cloud providers, and large enterprise IT
Search & Comparison IntentOften compared due to overlapping roles in system reliability and cloud infrastructureCompared for on-site vs remote operational responsibilities

The main difference is that Remote Reliability Engineers focus on cloud and system reliability remotely, while Remote Site Reliability Engineers may have some on-site duties related to infrastructure. Both roles require similar skills and certifications but differ in their work environment and specific responsibilities.

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

To thrive as a Remote Reliability Engineer, you need a strong background in systems engineering, software development, and infrastructure management, often supported by a degree in computer science or a related field. Proficiency with cloud platforms (such as AWS, Azure, or GCP), monitoring tools (like Prometheus, Grafana), and relevant certifications (e.g., AWS Certified DevOps Engineer) is highly valuable. Excellent problem-solving, communication, and collaboration skills are crucial for working effectively across distributed teams and responding to incidents. These abilities ensure system reliability, quick incident resolution, and seamless remote teamwork, which are vital for maintaining high service uptime and user satisfaction.

How do Remote Reliability Engineers typically collaborate with on-site teams to address urgent technical issues?

Remote Reliability Engineers often utilize a combination of video conferencing, instant messaging, and collaborative monitoring tools to stay closely connected with on-site teams. When urgent technical issues arise, they participate in real-time troubleshooting sessions, analyze system logs remotely, and may guide on-site staff through step-by-step resolution procedures. Building strong communication channels and regular check-ins are essential to ensure swift and effective collaboration, even across different time zones. This structure allows Remote Reliability Engineers to contribute significantly to system uptime while working from a distance.

What is a Remote Reliability Engineer?

A Remote Reliability Engineer is a professional who works from a remote location to ensure that systems, applications, or infrastructure are reliable, available, and performing well. Their responsibilities typically include monitoring system health, diagnosing issues, implementing preventative measures, and collaborating with teams to improve system reliability. They often use tools for automation, incident response, and performance monitoring, all while working offsite. This role is critical in minimizing downtime and ensuring a smooth user experience, especially for companies with complex technical environments. Remote Reliability Engineers must have strong problem-solving skills and be proficient in cloud technologies, automation, and incident management.
What cities near Commerce, MI are hiring for Remote Reliability Engineer jobs? Cities near Commerce, MI with the most Remote Reliability Engineer job openings:
Remote Reliability Engineer jobs near you
AI Infrastructure Engineer

AI Infrastructure Engineer

Utilidata

Ann Arbor, MI • Remote

$170K - $210K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 9 hours 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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