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Remote Mechanical Reliability Engineer Jobs (NOW HIRING)

NTT DATA Services

Site Reliability Engineer

Westlake, TX · On-site +1

$54.75 - $72.75/hr

We are currently seeking a Site Reliability Engineer to join our team in Westlake, Texas (US-TX), ... The starting pay range for this remote role is 85,000-140,000 This range reflects the minimum and ...

Apex Informatics

Site Reliability Engineer

$58.25 - $77.50/hr

Remote Duration: 6 Months (Contract) Details of the role: Need a Senior Site Reliability Engineer to work on Disaster Recovery (DR) initiative for different applications in the Cloud and onsite ...

Zortech Solutions

SRE Engineer

Newark, NJ · Remote

$58.25 - $77.50/hr

Join us as an Expert SRE to ensure operational excellence during the integration of merging systems ... failover mechanisms, load balancing, and redundancy across legacy and new systems. - Build ...

NTT DATA Services

Site Reliability Engineer

Westlake, TX · On-site +1

$54.75 - $72.75/hr

We are currently seeking a Site Reliability Engineer to join our team in Westlake, Texas (US-TX), ... The starting pay range for this remote role is 85,000-140,000 This range reflects the minimum and ...

Upstart

Senior Software Engineer, Site Reliability

OR · On-site +1

$57 - $75.75/hr

The Team Upstart's Site Reliability Engineering (SRE) team owns the reliability, resiliency, and ... Remote, San Mateo, Columbus, Austin, NY Time Zone Requirements - This team operates across all U.S ...

TELCOR Inc

Site Reliability Engineer

Lincoln, NE · On-site +1

$125K - $165K/yr

Site Reliability Engineer TELCOR Inc, a leading innovator in laboratory software, is looking for a ... remote. Copy and paste the following link into your browser to learn more about TELCOR and what it ...

Rootshell Enterprise Technologies, Inc.

SRE with FedRAMP

$58.25 - $77.50/hr

Remote Responsibilities Support client's FedRAMP environments as an embedded SRE. Ensure security, compliance, scalability, and reliability from day one, working in agile scrum teams. Design and ...

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All JobsRemote Mechanical Reliability Engineer Jobs

Remote Mechanical Reliability Engineer information

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$71.5K

$104.1K

$145K

How much do remote mechanical reliability engineer jobs pay per year?

As of Jun 25, 2026, the average yearly pay for remote mechanical reliability engineer in the United States is $104,148.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,500.00 and $118,000.00 per year, depending on experience, location, and employer.

Is it possible to work remotely as a mechanical engineer?

Remote work for mechanical reliability engineers is increasingly common, especially for tasks involving design, analysis, and reporting that can be performed using CAD software, simulation tools, and communication platforms. However, some roles requiring on-site inspections, maintenance, or equipment troubleshooting may necessitate physical presence. Overall, many companies offer remote or hybrid arrangements for suitable engineering tasks, often requiring strong technical skills and familiarity with remote collaboration tools.

What engineers make $500,000?

Senior mechanical reliability engineers with extensive experience, specialized skills in predictive maintenance, and certifications such as PE or Six Sigma can reach or exceed $500,000 annually, especially in industries like oil and gas, aerospace, or manufacturing. High-level roles often involve leadership, complex problem-solving, and advanced tools like FEA software, contributing to top-tier compensation.

What is the difference between Remote Mechanical Reliability Engineer vs Mechanical Maintenance Engineer?

AspectRemote Mechanical Reliability EngineerMechanical Maintenance Engineer
CredentialsBachelor's in Mechanical Engineering, certifications like RCM or FMEABachelor's in Mechanical Engineering or related field, certifications like HVAC or CMMS experience
Work EnvironmentPrimarily office-based, remote collaboration, data analysisOn-site plant or facility, hands-on equipment maintenance
Industry UsageManufacturing, energy, oil & gas, where reliability analysis is keyManufacturing, facilities management, industrial plants

The Remote Mechanical Reliability Engineer focuses on analyzing and improving equipment reliability remotely, often through data analysis and predictive maintenance. In contrast, the Mechanical Maintenance Engineer performs hands-on repairs and maintenance on-site. Both roles require mechanical engineering knowledge, but their work environments and daily tasks differ significantly.

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

To thrive as a Remote Mechanical Reliability Engineer, you need a solid background in mechanical engineering, experience with reliability analysis, and typically a bachelor's degree in engineering. Familiarity with reliability-centered maintenance (RCM) tools, predictive analytics software, and Computerized Maintenance Management Systems (CMMS) is often required. Strong problem-solving abilities, effective communication, and self-motivation are crucial soft skills for collaborating remotely and analyzing data independently. These competencies ensure accurate reliability assessments and effective maintenance strategies, driving equipment uptime and operational efficiency from a remote setting.

Will AI replace SRE jobs?

AI is unlikely to fully replace Mechanical Reliability Engineers, as their role requires specialized knowledge of machinery, systems, and troubleshooting that AI cannot fully replicate. Instead, AI tools are increasingly used to assist engineers by automating routine tasks, analyzing data, and improving predictive maintenance. SREs will continue to adapt by integrating AI and automation into their workflows to enhance reliability and efficiency.

How does a Remote Mechanical Reliability Engineer typically collaborate with onsite teams to address equipment issues?

Remote Mechanical Reliability Engineers frequently work alongside onsite engineers, maintenance staff, and operations teams to troubleshoot and resolve equipment reliability concerns. Collaboration is facilitated through virtual meetings, real-time data sharing platforms, and remote monitoring tools. Clear communication and effective documentation are key, as remote engineers must interpret equipment data and provide actionable recommendations while relying on local teams for physical inspections and repairs. Building strong relationships with onsite personnel is essential for timely problem-solving and continuous improvement.

What does a Remote Mechanical Reliability Engineer do?

A Remote Mechanical Reliability Engineer is responsible for ensuring the reliability and optimal performance of mechanical systems and equipment, often working from a remote location. They analyze data, identify potential failure points, develop maintenance strategies, and recommend design improvements to increase equipment uptime and lifespan. These engineers collaborate with onsite teams, use specialized software for monitoring, and may also support troubleshooting and root cause analysis remotely. Their work helps organizations minimize unplanned downtime and reduce maintenance costs.

What engineers make $300,000 a year?

Senior mechanical reliability engineers with extensive experience, advanced certifications, and specialized skills in predictive maintenance and asset management can earn $300,000 or more annually, especially in industries like oil and gas, aerospace, or manufacturing. High-level roles often require leadership responsibilities, advanced degrees, and proficiency with reliability tools such as FMEA or RCM.
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Remote Mechanical Reliability Engineer jobs near you
Infographic showing various Remote Mechanical Reliability Engineer job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $104,148 per year, or $50.1 per hour.
AI Reliability Engineer (AI SRE) - Q126

AI Reliability Engineer (AI SRE) - Q126

R2 Technologies Corporation

Alpharetta, GA • On-site

$55.75 - $74/hr

Full-time

Posted 19 days ago

Job description

Overview:
Job Title: AI Reliability Engineer (AI SRE)
Company: R2 Technologies
Location: Alpharetta, GA (Hybrid / Remote Options Available)
Employment Type: Full-Time / Contractual
About R2 Technologies: R2 Technologies is a Certified Minority Business Enterprise (MBE) headquartered in Alpharetta, GA. With over two decades of experience across global markets, we have built a reputation as a trusted partner for IT staffing excellence and cutting-edge digital product innovation. We are driven by innovation and operate on a simple philosophy: "We deliver what we promise, and we promise only what we can deliver." Beyond providing top-tier IT talent, R2 builds cutting-edge proprietary solutions like SmartEnt-an Enterprise AI & IoT Intelligence Platform utilizing advanced NLP and AI technologies. By partnering closely with our clients, we deliver technology-driven outcomes that are realistic, measurable, and impactful.
Job Summary: As enterprise AI shifts from prototypes to mission-critical production systems, we need engineers who can guarantee stability. R2 Technologies is seeking an AI Reliability Engineer to merge traditional Site Reliability Engineering (SRE) with LLM operations. You will be the guardian of our production AI, responsible for monitoring foundation models for performance drift, optimizing token usage and GPU costs, and ensuring high-availability inference for our SmartEnt platform.
Key Responsibilities: * Deploy, scale, and manage LLM inference servers (e.g., vLLM, Ray Serve, NVIDIA Triton) on Kubernetes across multi-cloud environments.
  • Implement comprehensive observability, logging, and tracing for complex agentic workflows using platforms like LangSmith, MLflow, or Weights & Biases (Weave).
  • Monitor production models for data drift, hallucination rates, and latency spikes, implementing automated rollback or model-routing strategies when necessary.
  • Optimize cloud infrastructure to balance GPU utilization, inference speed, and token cost (FinOps for AI).
  • Automate infrastructure provisioning (IaC) and CI/CD pipelines specifically tailored for machine learning models and fine-tuned adapters.
  • Actively utilize AI-assisted coding tools (GitHub Copilot, Cursor) to automate infrastructure management and incident response scripting.

Qualifications: * Up to 3 years of hands-on experience in SRE, DevOps, MLOps, or Cloud Infrastructure.
  • Strong proficiency in containerization and orchestration (Docker, Kubernetes, Helm).
  • Experience configuring and scaling GPU-backed workloads in cloud environments (AWS, Azure, or GCP).
  • Familiarity with LLM observability tools and trace-level debugging of AI applications.
  • Proven experience or strong familiarity working alongside AI coding assistants to enhance productivity.
  • Scripting skills in Python and Bash, with a strong focus on system reliability, automation, and cost-optimization.

Skills:
Reliability Engineering,Kubernetes

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