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Ai Reliability Engineer Jobs in Worcester, MA (NOW HIRING)

Hologic

Senior Applied AI Engineer

Marlborough, MA · On-site

$108K - $148K/yr

Senior Applied AI Engineer Role Summary We are hiring a Senior Applied AI Engineer to help us find ... Weigh trade-offs like cost, performance, reliability, and maintainability, and explain them in ...

Hologic, Inc.

Senior Applied AI Engineer

Marlborough, MA · On-site

$94.30 - $147.40/hr

Senior Applied AI Engineer Role Summary We are hiring a Senior Applied AI Engineer to help us find ... Weigh trade-offs like cost, performance, reliability, and maintainability, and explain them in ...

Hologic Inc.

Senior Applied AI Engineer

Marlborough, MA · On-site

$108K - $148K/yr

Senior Applied AI Engineer Role Summary We are hiring a Senior Applied AI Engineer to help us find ... Weigh trade-offs like cost, performance, reliability, and maintainability, and explain them in ...

Nubiral

Cloud Engineer (GCP & AWS)

Ayer, MA · On-site

$120 - $180/hr

Guiar a ingenieros de menor seniority, promover la adopci f3n de pr e1cticas DevOps/SRE y ... AI (Vertex AI, AWS SageMaker, Databricks). * Conocimientos de arquitectura en Microsoft Azure u ...

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All JobsAi Reliability Engineer JobsAi Reliability Engineer Jobs in Worcester, MA

Ai Reliability Engineer information

See Worcester, MA salary details

$60.9K

$117.7K

$140.7K

How much do ai reliability engineer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for ai reliability engineer in Worcester, MA is $117,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,300.00 and $128,700.00 per year, depending on experience, location, and employer.

What is an AI reliability engineer?

AI Reliability Engineers are professionals responsible for ensuring that artificial intelligence systems function reliably, safely, and effectively over time. They work on monitoring AI models in production, identifying and mitigating potential failures, and improving the robustness of AI systems. Their tasks often include testing, validation, performance monitoring, and implementing best practices for maintaining AI infrastructure. By focusing on reliability, they help organizations deploy AI solutions that are dependable and trustworthy in real-world environments.

What are some common challenges AI reliability engineers face when ensuring model robustness in production environments?

Ai Reliability Engineers often encounter challenges such as monitoring AI model performance for drift or unexpected behavior, managing data quality issues, and implementing automated alerting systems for anomalies. In production, it's crucial to ensure that AI models operate consistently and remain reliable under varying conditions and data inputs. Collaborating closely with data scientists, software engineers, and DevOps teams is essential to address these challenges and to continuously improve model reliability and uptime.

What are the key skills and qualifications needed to thrive as an AI reliability engineer, and why are they important?

To thrive as an AI Reliability Engineer, you need a solid background in computer science or engineering, expertise in AI/ML concepts, and experience with software testing and reliability methodologies. Familiarity with tools like TensorFlow, PyTorch, CI/CD pipelines, and reliability testing frameworks, along with certifications in cloud platforms (e.g., AWS Certified Machine Learning), is highly valuable. Analytical thinking, problem-solving abilities, and strong collaboration skills set top performers apart in this role. These skills ensure robust, dependable AI systems that meet performance standards and maintain trust in critical applications.

What is the difference between Ai Reliability Engineer vs Data Scientist?

AspectAi Reliability EngineerData Scientist
Required CredentialsBachelor's or master's in CS, engineering, or related; certifications in AI/MLBachelor's or master's in CS, statistics, or related; certifications in data analysis or ML
Work EnvironmentTech companies, AI-focused teams, engineering departmentsResearch labs, tech firms, analytics teams
Employer & Industry UsageAI product development, machine learning systems, reliability testingData analysis, predictive modeling, business insights

While both roles involve AI and ML, Ai Reliability Engineers focus on ensuring AI system robustness and uptime, whereas Data Scientists analyze data to generate insights and models. The roles often collaborate but serve different primary functions within AI projects.

What are popular job titles related to Ai Reliability Engineer jobs in Worcester, MA?

For Ai Reliability Engineer jobs in Worcester, MA, the most frequently searched job titles are:

What job categories do people searching Ai Reliability Engineer jobs in Worcester, MA look for?

The top searched job categories for Ai Reliability Engineer jobs in Worcester, MA are:

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Cities near Worcester, MA with the most Ai Reliability Engineer job openings:

Ai Reliability Engineer jobs near you

Senior Software Engineer, Infrastructure Automation and Distributed Systems

Nvidia

Westford, MA • On-site

$112K - $153K/yr

Full-time

Re-posted 6 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies

Job description

We are seeking Systems Engineers and Software Engineers interested in building and running reliable large scale infrastructure platform services. In this organization, you will ensure that our internal and external facing EDA services atop of NVIDIA hardware are running as reliably as needed. NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hard-working people in the world working for us. Are you creative and autonomous? Do you love a challenge? If so, we want to hear from you.

What you'll be doing:

  • Design, build, deploy, and run infrastructure services & manage the software life cycle in scope to meet our business goals.

  • Participate in the definition of our internal facing service level objectives and error budgets as part of our overall observability strategy.

  • Eliminate toil or automate it where the ROI of building and maintaining automation is worth it.

  • Practice sustainable blameless incident prevention and incident response while being a member of an oncall rotation.

  • Consult with and provide consultation for peer teams on systems design best practices.

What we need to see:

  • BS degree in Computer Science or a related technical field involving coding (e.g., physics or mathematics) or equivalent experience.

  • 12+ years of relevant experience.

  • A track record showing a good balance between initiating your own projects, convincing others to collaborate with you and collaborating well on projects initiated by others.

  • Experience with infrastructure automation and distributed systems design developing tools for running large scale private or public cloud system in production.

  • Experience in one or more of the following: Python, Go, Perl or Ruby.

  • In depth knowledge in one or more of Linux, Networking, Storage, and Containers.

Ways to stand out from the crowd:

  • Systematic problem-solving approach, coupled with strong communication skills and a sense of ownership and drive. Experience accelerating positive impact to the business using coding assistant(s), MCP servers, or AI agents.

  • Experience working with or developing bare metal as a service (BMaaS) associated systems.

  • Experience working with or developing multi-cloud infrastructure services and running private or public cloud systems based on one or more of Kubernetes, OpenStack, Docker or Slurm.

  • Experience teaching reliability (e.g SRE) or more general cloud systems good practices to peers or to other companies (e.g CRE).

  • Background with NVIDIA Collective Communication Library (NCCL).

No prior experience having worked in a team of any particular name or having worked in a ML/AI focused team are required but also a nice to have.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until September 4, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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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

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