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Temporary Machine Learning Scientist Jobs in Raleigh, NC

LexisNexis

Machine Learning Engineer Lead

Raleigh, NC

$115K - $192K/yr

The company employs over 2,000 technologists, data scientists, and experts to develop, test, and ... We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML ...

RELX

Machine Learning Engineer Lead

Raleigh, NC · On-site

$115K - $192K/yr

The company employs over 2,000 technologists, data scientists, and experts to develop, test, and ... We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML ...

LexisNexis

Machine Learning Engineer Lead

Raleigh, NC

$115K - $192K/yr

The company employs over 2,000 technologists, data scientists, and experts to develop, test, and ... We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML ...

Peter Millar

Senior Data Scientist

Durham, NC

The Senior Data Scientist expands Peter Millar's data science capacity beyond customer analytics ... Operating at the intersection of applied machine learning, business strategy, and the modern data ...

Labcorp

Associate Data Scientist

Durham, NC · Hybrid

$57K - $57K/yr

Build, test, and deploy statistical and machine learning models to support business and scientific ... Employees regularly scheduled to work less than 20 hours, Casual, Intern, and Temporary employees ...

Tata Consultancy Services

AI ML Data Scientist

Cary, NC · On-site

Required : • BACHELOR OF COMPUTER SCIENCE • 8 - 10 Years of experience • Machine Learning techniques • Unsupervised - K-means Clustering, PCA - Dimension Reduction, Kernel Density Estimations ...

LexisNexis

Senior Machine Learning Engineer III

Raleigh, NC · Hybrid

$118K - $219K/yr

Are you looking to develop your Machine Learning Engineer career? Do you enjoy coaching others to ... You will partner with Data Scientists to turn validated models and prototypes into reliable, high ...

Siemens

Principal Data Scientist

Raleigh, NC · On-site

$122K - $210K/yr

Beyond leading our core data science practice - predictive maintenance, asset health, failure ... Operationalize machine learning systems: Work with ML engineering and product teams to deploy ...

Cigna

Data Science Director - Remote

Raleigh, NC · On-site +1

As the Data Science Director for Pricing & Underwriting, you will lead high-impact teams that build ... Provide technical leadership across machine learning, statistical modeling, feature engineering ...

New

RELX

Principal Machine Learning Engineer I

Raleigh, NC · On-site

$136K - $252K/yr

The company employs over 2,000 technologists, data scientists, and experts to develop, test, and ... We are seeking a Principal Machine Learning Engineer to design, build, and operate scalable AI/ML ...

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Temporary Machine Learning Scientist information

What is the difference between Temporary Machine Learning Scientist vs Data Scientist?

AspectTemporary Machine Learning ScientistData Scientist
CredentialsTypically requires a master's or PhD in computer science, data science, or related fields; experience with machine learning frameworksUsually holds a bachelor's or master's in data science, statistics, or related fields; strong analytical skills
Work EnvironmentProject-based, often contract roles in tech, finance, or healthcare companiesFull-time or contract roles across various industries, focusing on data analysis and insights
Employer UsageHired for specialized machine learning projects, prototypes, or research tasksEngaged in data analysis, reporting, and building predictive models

In summary, a Temporary Machine Learning Scientist focuses on developing and implementing machine learning models on a temporary basis, often requiring advanced credentials and specialized skills. In contrast, a Data Scientist has a broader role in analyzing data and generating insights, with less emphasis solely on machine learning techniques.

What are Temporary Machine Learning Scientists?

Temporary Machine Learning Scientists are professionals hired on a short-term basis to develop, implement, and optimize machine learning models within an organization. They typically work on specific projects or to fill a temporary gap in expertise, often collaborating with data scientists, engineers, and stakeholders. Their responsibilities may include data preprocessing, feature engineering, model selection, and evaluation. These roles are ideal for projects with defined timelines or exploratory research that does not require a permanent hire. Temporary contracts can range from a few months to a year, depending on the project's scope and needs.

What types of projects do Temporary Machine Learning Scientists typically work on, and how do they integrate with existing teams?

Temporary Machine Learning Scientists are often brought in to support short-term projects such as data analysis, model prototyping, or improving existing machine learning pipelines. Their work usually involves collaborating closely with data engineers, software developers, and product managers to ensure seamless integration of models into production systems. Since the role is temporary, effective communication and quick adaptation to the team's workflow are crucial. These scientists are expected to rapidly understand the company's data and objectives, deliver actionable insights, and document their work for team continuity after their contract ends.

What are the key skills and qualifications needed to thrive as a Temporary Machine Learning Scientist, and why are they important?

To thrive as a Temporary Machine Learning Scientist, you typically need advanced knowledge of machine learning algorithms, data analysis, programming skills (such as Python or R), and a relevant degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and tools for data processing and model deployment is often required, along with experience using cloud platforms such as AWS or Azure. Strong problem-solving abilities, adaptability, and effective communication skills help you quickly integrate into teams and deliver results on short-term projects. These skills ensure you can efficiently contribute to impactful solutions and adapt to rapidly changing project requirements.
What are the most commonly searched types of Machine Learning Scientist jobs in Raleigh, NC? The most popular types of Machine Learning Scientist jobs in Raleigh, NC are:
What are popular job titles related to Temporary Machine Learning Scientist jobs in Raleigh, NC? For Temporary Machine Learning Scientist jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Temporary Machine Learning Scientist jobs in Raleigh, NC look for? The top searched job categories for Temporary Machine Learning Scientist jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Temporary Machine Learning Scientist jobs? Cities near Raleigh, NC with the most Temporary Machine Learning Scientist job openings:
Temporary Machine Learning Scientist jobs near you
Infographic showing various Temporary Machine Learning Scientist job openings in Raleigh, NC as of July 2026, with employment types broken down into 17% Internship, and 83% Full Time. Highlights an 68% In-person, and 32% Remote job distribution.
Machine Learning Engineer Lead

Machine Learning Engineer Lead

LexisNexis

Raleigh, NC

$115K - $192K/yr

Full-time

Re-posted 29 days ago

LexisNexis rating

7.6

Company rating: 7.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

160th of 449 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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