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Contract Machine Learning Testing Jobs in North Carolina

LexisNexis

Machine Learning Engineer Lead

Raleigh, NC · On-site

$115K - $192K/yr

We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML ... Establish engineering best practices for ML system design, testing, and deployment. * Conduct ...

LexisNexis

Machine Learning Engineer Lead

Raleigh, NC

$115K - $192K/yr

We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML ... Establish engineering best practices for ML system design, testing, and deployment. * Conduct ...

CRC Group

Software Engineer - Machine Learning

Charlotte, NC · On-site

$95K - $130K/yr

... the machine learning function at a market-leading insurance company. As one of the first data ... Responsible for design, developing, and maintaining automated unit testing, and supporting ...

RELX

Principal Machine Learning Engineer I

Raleigh, NC · On-site

$136K - $252K/yr

We are seeking a Principal Machine Learning Engineer to design, build, and operate scalable AI/ML ... Establish engineering best practices for ML system design, testing, and deployment. * Conduct ...

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All JobsContract Machine Learning Testing JobsContract Machine Learning Testing Jobs in North Carolina

Contract Machine Learning Testing information

What is the difference between Contract Machine Learning Testing vs Contract Data Analyst?

AspectContract Machine Learning TestingContract Data Analyst
Required CredentialsKnowledge of ML algorithms, programming skills (Python, R), understanding of testing frameworksStatistical skills, data visualization, proficiency in SQL and Excel
Work EnvironmentTech companies, AI startups, consulting firmsBusiness intelligence teams, marketing agencies, finance firms
Employer & Industry UsagePrimarily in AI/ML development projects across tech and research sectorsData-driven decision making in various industries like finance, marketing, and healthcare

Contract Machine Learning Testing focuses on evaluating and validating ML models for accuracy and performance, requiring technical skills in algorithms and programming. Contract Data Analysts interpret data, generate reports, and support business decisions using statistical tools. While both roles involve working with data, Machine Learning Testing is more technical and specialized in AI models, whereas Data Analysts focus on broader data analysis and reporting.

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Machine Learning Engineer Lead

Machine Learning Engineer Lead

LexisNexis

Raleigh, NC • On-site

$115K - $192K/yr

Full-time

Posted 4 days ago

LexisNexis rating

7.6

Company rating: 7.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

162nd of 451 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 Machine Learning Engineer Lead 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.

In this role you will be a hands-on engineer and leader that will lead a high-performing team of 4-5 ML engineers, drive platform-level decisions, and ensure enterprise-grade scalability, reliability, and responsible AI compliance.

Responsibilities:

  • Lead, mentor, and grow a team of 4-5 ML engineers.

  • 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

  • 8-10 years of Machine Learning/Software Engineer experience

  • 2-3 years of people management 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: $115,400 - $192,300. 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.

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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.

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