ZipRecruiter

Log In

1

Mlops Machine Learning Engineer Jobs in Raleigh, NC

RELX

Principal Machine Learning Engineer I

Raleigh, NC

$136K - $252K/yr

We are seeking a Principal Machine Learning Engineer to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products.

Apple

AIML - Staff Machine Learning Engineer

Cary, NC · On-site

Building this system requires deep expertise in a myriad of cutting edge fields: search, natural language understanding, data engineering, machine learning, privacy preserving system design, and more.

Apple

AIML - Staff Machine Learning Engineer

Cary, NC

$216K - $394K/yr

Building this system requires deep expertise in a myriad of cutting edge fields: search, natural language understanding, data engineering, machine learning, privacy preserving system design, and more.

Apple

AIML - Staff Machine Learning Engineer

Cary, NC

$216K - $394K/yr

Building this system requires deep expertise in a myriad of cutting edge fields: search, natural language understanding, data engineering, machine learning, privacy preserving system design, and more.

Qualcomm

Machine Learning Compiler Engineer

Raleigh, NC · On-site

$80K - $106K/yr

Engineering Group, Engineering Group > Machine Learning Engineering General Summary: If you're interested in advancing and applying mathematics, programming languages theory, and advanced algorithms ...

Qualcomm

Machine Learning Compiler

Raleigh, NC · On-site

$160K - $240K/yr

Engineering Group, Engineering Group > Machine Learning Engineering General Summary: Lead a team of engineers focused on advancing machine learning compiler technologies for cutting-edge AI ...

Varsity Tutors

Machine Learning Tutor

Chapel Hill, NC · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Berriehill Research

Senior AI Systems Engineer

Raleigh, NC · On-site +1

$92K - $126K/yr

Operationalize machine learning workflows and support AI-enabled applications from development ... Build and maintain CI/CD and MLOps pipelines for model packaging, testing, deployment, rollback ...

Varsity Tutors

Machine Learning Tutor

Raleigh, NC · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Durham, NC · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

next page

Showing results 1-20

All JobsMlops Machine Learning Engineer JobsMlops Machine Learning Engineer Jobs in Raleigh, NC

Mlops Machine Learning Engineer information

See Raleigh, NC salary details

$30.6K

$125.2K

$188.1K

How much do mlops machine learning engineer jobs pay per year?

As of Jul 9, 2026, the average yearly pay for mlops machine learning engineer in Raleigh, NC is $125,174.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,700.00 and $150,700.00 per year, depending on experience, location, and employer.

What does an MLOps Machine Learning Engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

How does an MLOps Machine Learning Engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

What is the difference between Mlops Machine Learning Engineer vs Data Scientist?

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

What are the key skills and qualifications needed to thrive as an MLOps Machine Learning Engineer, and why are they important?

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.
What are popular job titles related to Mlops Machine Learning Engineer jobs in Raleigh, NC? For Mlops Machine Learning Engineer jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Mlops Machine Learning Engineer jobs in Raleigh, NC look for? The top searched job categories for Mlops Machine Learning Engineer jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Mlops Machine Learning Engineer jobs? Cities near Raleigh, NC with the most Mlops Machine Learning Engineer job openings:
Mlops Machine Learning Engineer jobs near you
Principal Machine Learning Engineer I

Principal Machine Learning Engineer I

LexisNexis

Raleigh, NC • On-site

$136K - $252K/yr

Full-time

Re-posted 28 days ago

LexisNexis rating

7.6

Company rating: 7.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

155th of 442 rated business services

Job description

About our Team
LexisNexis Legal & Professional, which serves customers in more than 150 countries with 11,800 employees worldwide, is part of RELX (www.relx.com), a global provider of information-based analytics and decision tools for professional and business customers. Our company has been a long-time leader in deploying AI and advanced technologies to the legal market to improve productivity and transform the overall business and practice of law, deploying ethical and powerful generative AI solutions with a flexible, multi-model approach that prioritizes using the best model from today's top model creators for each individual legal use case. The company employs over 2,000 technologists, data scientists, and experts to develop, test, and validate solutions in line with RELX Responsible AI Principles (https://stories.relx.com/responsible-ai-principles/index.html).
About the Role
Do you love collaborating with teams to solve complex technical problems?
We are seeking a Principal Machine Learning Engineer to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products. This role combines deep ML expertise with distributed systems engineering and AI platform development.
You will play a key role in developing enterprise-grade AI systems, including large language model (LLM) infrastructure, retrieval-augmented generation (RAG) pipelines, and autonomous agent frameworks designed for complex large unstructured data.
Responsibilities:
  • Provide architectural direction and code-level guidance.
  • Establish engineering best practices for ML system design, testing, and deployment.
  • Conduct design reviews, performance reviews, and technical roadmap planning.
  • Architect distributed ML systems serving multiple global products.
  • Standardize infrastructure patterns for LLM serving and retrieval systems.
  • Define and implement enterprise-ready agentic frameworks.
  • Architect multi-step reasoning systems.
  • Lead decisions on deterministic workflows vs. autonomous agents.
  • Implement guardrails, safety layers, and traceability mechanisms.
  • Develop evaluation frameworks to measure reasoning quality, hallucination rates, and reliability.
  • Establish CI/CD standards for ML lifecycle management.
  • Ensure compliance with enterprise data governance and responsible AI standards.

Requirements
  • 10 + years of Machine Learning/Software Engineer experience
  • Master's degree or bachelor's degree, computer science degree is highly desirable.
  • Strong software engineering background with experience in building system design, architecting AI feature/products that caters large number of users and deals with large volume of unstructured data
  • Experience with ML deployment to production
U.S. National Base Pay Range: $136,100 - $252,800. Geographic differentials may apply in some locations to better reflect local market rates.This job is eligible for an annual incentive bonus.
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.
Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here
Please read our Candidate Privacy Policy.
We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
USA Job Seekers:
EEO Know Your Rights.

What LexisNexis employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply