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Scientific Machine Learning Jobs in Raleigh, NC (NOW HIRING)

RELX

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 ...

LexisNexis

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 ...

RELX Group plc

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 · 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 ...

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 ...

LexisNexis

Director, Data Sciences

Raleigh, NC · On-site

The Director, Data Sciences is responsible for leading a team of data scientists and developing ... Oversee advanced data analysis, modeling, and machine learning to develop predictive and ...

TEKsystems

Principal Data Scientist

Raleigh, NC

$75 - $90/hr

VSCODE and PYCHARM Have communication skills 5+ years of experience in AI and machine learning Deep ... Details Python,Data science,Machine learning,Artificial intelligence Additional Skills ...

Deloitte

Senior AI Engineer - SFL Scientific

Raleigh, NC

$101K - $139K/yr

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

Korn Ferry

Director, Data Sciences

Raleigh, NC · On-site

The Director, Data Sciences is responsible for raising data-driven decision making within a ... Oversee advanced data analysis, modeling, and machine learning to develop predictive and ...

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 ...

RELX

Principal Machine Learning Engineer I

Raleigh, NC

$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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Scientific Machine Learning information

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How much do scientific machine learning jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for scientific machine learning in Raleigh, NC is $30.60, according to ZipRecruiter salary data. Most workers in this role earn between $18.70 and $39.04 per hour, depending on experience, location, and employer.

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are the key skills and qualifications needed to thrive as a scientific machine learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What are some common challenges faced by professionals in scientific machine learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

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

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in Raleigh, NC?

For Scientific Machine Learning jobs in Raleigh, NC, the most frequently searched job titles are:

What job categories do people searching Scientific Machine Learning jobs in Raleigh, NC look for?

The top searched job categories for Scientific Machine Learning jobs in Raleigh, NC are:

What cities near Raleigh, NC are hiring for Scientific Machine Learning jobs?

Cities near Raleigh, NC with the most Scientific Machine Learning job openings:

Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in Raleigh, NC as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 22% Part Time, 1% Temporary, and 5% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $63,645 per year, or $30.6 per hour.

Machine Learning Engineer Lead

RELX

Raleigh, NC

$115K - $192K/yr

Full-time

Re-posted 7 days ago

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.

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