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

WGU

Senior Machine Learning Engineer

Raleigh, NC

$157K - $243K/yr

Master's degree in Computer Science, Software Engineering, Data Science, Machine Learning, Mathematics, Physics, or a related field; or equivalent relevant experience. * 5+ years of software ...

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 ...

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 · 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 ...

NCSU

Assistant Research Professor

Raleigh, NC · On-site

Develop and implement advanced mathematical, statistical, and machine learning models to analyze complex biological and scientific datasets. * Design interpretable dynamical systems frameworks using ...

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 ...

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 ...

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Scientific Machine Learning information

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How much do scientific machine learning jobs pay per hour?

As of Jun 18, 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.

Is ML a high paying job?

Scientific Machine Learning roles typically offer high salaries due to the specialized skills required, such as expertise in deep learning, data analysis, and programming with tools like Python and TensorFlow. Compensation varies by industry, experience, and location but generally exceeds average tech salaries for comparable roles.

Which 3 jobs will survive AI?

Scientific Machine Learning professionals will likely continue to be in demand due to their expertise in developing and applying AI models to complex scientific problems. Roles such as data scientists, AI researchers, and machine learning engineers are expected to persist because they require specialized knowledge, critical thinking, and ongoing innovation that AI tools complement rather than replace. These jobs often involve interdisciplinary skills, programming, and understanding of domain-specific data, making them more resilient to automation.

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 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.

How much does a machine learning scientist make?

A machine learning scientist typically earns between $90,000 and $150,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in deep learning or natural language processing can earn higher salaries, often exceeding $180,000.

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 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.

Is 40 too late for data science?

Scientific Machine Learning roles often value skills and experience over age, and many professionals transition into data science or machine learning at various stages of their careers. Learning relevant tools like Python, TensorFlow, or scikit-learn and gaining practical experience can help regardless of age, making 40 not too late to pursue this field.
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 June 2026, with employment types broken down into 78% Full Time, and 22% Part Time. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $63,645 per year, or $30.6 per hour.
Director of AI & Machine Learning

Director of AI & Machine Learning

Accentuate Staffing

Morrisville, NC • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Accentuate Staffing is seeking a Director of AI & Machine Learning with strong strategic vision, deep hands‑on technical expertise, and a proven ability to build and lead high‑performing teams delivering scalable, ethical AI solutions. The ideal candidate will also excel at aligning advanced machine learning capabilities with business objectives and driving innovation across the organization.

Responsibilities:

Manage and Develop Staff

  • Responsible for establishing and implementing a safe working environment that meets all licensure, regulatory, and accreditation requirements
  • Lead, train and develop the members of the Artificial Intelligence team and assist them in delivering clear and actionable information
  • Develops plans to monitor and manage staff productivity and success in meeting assigned objectives
  • Ensure staff are well trained in policies, procedures, and business processes
  • Reviews, makes recommendations and implements the needed systems and tools to successfully fulfill corporate objectives and to support staff and team members
  • Lead the identification and development of the Artificial Intelligence Team roles, configuration and recruitment
  • Provide solution design guidance to the Artificial Intelligence team, ensuring delivery of best‑in‑class solutions for the challenges at hand
  • Leads ongoing coaching and mentoring to staff on new technology tools and practices, including change management practices, to support a learning environment to advance team skills
  • Ensure all staff are treated with respect and dignity
  • Ensure standards are transparent and applied consistently, impartially, and ethically over time and across all staff members
  • Work to resolve conflicts and disputes, ensuring that all participants are given a voice
  • Effectively communicate feedback and provide ongoing coaching and mentoring to staff and support a learning environment to advance team skills and professional development
  • Cultivate and encourage efforts to expand cross‑team collaboration and partnership

Oversee Artificial Intelligence Operations

  • Lead the development and implementation of AI/ML initiatives across the organization, ensuring alignment with business objectives and strategies
  • Collaborate with cross‑functional teams to design, build, and deploy AI/ML models and solutions
  • Oversee the collection, processing, and analysis of large datasets from various sources to fuel AI/ML models
  • Develop and maintain relationships with external partners, vendors, and academia to stay ahead of the curve in AI/ML innovation
  • Ensure the successful deployment of AI/ML solutions across the organization, including training, support, and ongoing maintenance
  • Foster a culture of innovation and experimentation, encouraging collaboration and knowledge sharing across the organization
  • Develop, define, and enforce best practices, processes, policies and system security to ensure alignment with all corporate strategy and goals

Communication and Collaboration

  • Lead in a consultant role in advising executive and senior leadership on complex and high‑risk strategic and contractual operational IT initiatives
  • Collaborate with leaders across the organization to help them understand and identify the value drivers to improve business operations and meet organizational objectives
  • Communicate corporate initiatives with both technical and non‑technical executives and other team members, using active leadership skills across project team and the business community
  • Develop cross‑departmental teams and analytics business application expertise throughout the organization
Requirements:
  • Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics or a related technical field and 5 (five) years of experience with increasing responsibilities in managing and supporting information technology
  • Strong technical expertise in AI/ML algorithms, data modeling, and data engineering
  • Excellent analytical, strategic conceptual thinking, strategic planning and execution skills
  • Experience with AI/ML platforms and tools, such as TensorFlow or PyTorch
  • Experience with GenAI Models, such as Meta Llama and Mistral AI
  • Excellent verbal and written communication skills, including the ability to explain AI concepts
  • Planning and organizational skills
  • Demonstrated skills in Microsoft Project, Excel, Word, and PowerPoint and other commonly used software and data analysis software
  • Proven track record of delivering successful AI/ML projects and solutions
  • Strong business acumen, including industry, domain‑specific knowledge of the enterprise and its business units
  • Ability to identify and calculate risk levels and implement mitigation techniques.
  • Ability to work effectively with, manage, motivate and get results from diverse stakeholders, including executive and senior leadership.
  • Ability to work across multiple, distributed, functional groups
  • Specific experience with clinical management information systems is a plus.
  • Artificial Intelligence and Machine Learning
  • Productivity and reporting applications such as Data Analytics
  • Business processes and their interrelationship gained through 5 (five) or more years of related experience
  • Analyzing and resolving complex issues, both logical and interpersonal
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