North Carolina Machine Learning Masters Programs

Machine Learning Engineers Have a Big Impact on North Carolina’s Economy

Anchored by Research Triangle Park’s ecosystem of world-class research institutions and tech companies, North Carolina is seeing a significant amount of tech development.

• Duke University’s AI Health Consortium and UNC–Chapel Hill’s AI Initiative advance work in biomedical AI, cybersecurity, and autonomous systems.
• NC State’s Institute for Advanced Analytics churns out data scientists year-round.
• SAS Institute’s global headquarters in Cary drives enterprise AI
• Apple’s Maiden data center runs on renewable power
• Google’s Lenoir facility supports cloud services
• Microsoft maintains an Azure presence serving public-sector workloads.

The state’s public-private partnerships further accelerate innovation.

The North Carolina Department of Commerce’s Tech Talent Action Plan fosters collaborations between startups and established firms in Charlotte and Raleigh, and the City of Durham’s AI+ accelerator connects entrepreneurs with leading employers.

Despite this growth, companies still face shortages of skilled machine learning engineers and data scientists.

The programs below provide the advanced training needed to fill these in-demand roles.

2026 Best Schools for Masters in Machine Learning Degrees in North Carolina

If you're looking for the best schools for a master's in machine learning in North Carolina, you're in the right place. At mastersinmachinelearning.org, we've done the research to help you find top programs that fit your needs. Our rankings are based on a thorough evaluation of factors like curriculum quality, faculty expertise, and career outcomes. For more details on how we rank these schools, check out our https://www.mastersinmachinelearning.org/ranking-methodology/ page. Start your journey today and explore the opportunities waiting for you in this exciting field.

#1

Duke University

Durham, NC - Private 4-year - duke.edu

Master's - Master of Engineering in Artificial Intelligence for Product Innovation

Concentration: Machine Learning - Online Learning - Visit Website

Duke University's Master of Engineering in Artificial Intelligence for Product Innovation with a Machine Learning concentration is a top-tier online program designed for STEM professionals. It emphasizes practical skills through hands-on projects and industry partnerships, preparing graduates for leadership in sectors like tech and healthcare. The program offers flexible 12 to 24-month options and requires a background in engineering, science, or technology. Admissions may require an entrance exam such as the GRE, though specific requirements should be verified on the university's website.

• Concentration in Machine Learning.
• Flexible 12, 16, 24-month options.
• Hands-on real-world projects.
• Industry collaborations included.
• Background in STEM required.

#2

Carolina University

Winston-Salem, NC - Private 4-year - carolinau.edu

Master's - Master of Science in Innovation

Concentration: machine learning - Online & Campus Based - Visit Website

Carolina University's Master of Science in Innovation with a concentration in Machine Learning is a two-year hybrid program that combines online and in-person learning for flexibility. It focuses on developing advanced skills in machine learning applications, innovation processes, and leadership across technology and business sectors. Admission requires a bachelor's degree with a minimum 2.5 GPA, official transcripts, and a completed application; no entrance exam is specified as required. Graduates are prepared for diverse roles, emphasizing practical outcomes and team management in innovative environments.

• 2 Year Program
• Hybrid learning format
• Focus on Machine Learning
• Requires bachelor's degree
• 2.5 GPA minimum
• Official transcripts needed
• Diverse sector applications
• Leadership in innovation
• Balanced leadership structures
• Advanced innovation skills

*Postsecondary education statistics from IPEDS 2023, NCES.

Local Job Market Analysis for Graduates in NC

What Skill Sets Employers Looking For in North Carolina?

North Carolina’s machine learning job market spans diverse industries from biotechnology to financial services, offering exceptional opportunities for graduates with ML expertise. Based on current job postings, here’s what employers are seeking, organized by skillset and compensation levels.

Core Technical Skills in High Demand

Programming and Framework Mastery

Syngenta in Durham offers positions for AI Machine Learning Engineers in their agricultural biotechnology division, requiring PhD in Bioinformatics, Computer Science, or Data Science with biology focus. They focus on knowledge graph construction and graph-based ML techniques for biological research, emphasizing expertise in AWS SageMaker ecosystem and Snowflake integration.

Red Hat in Raleigh provides exceptional compensation of $170,770-$312,730 for Senior/Principal ML Engineers contributing to PyTorch upstream community. They require experience in open source AI projects with existing PyTorch contributions being a strong plus, focusing on integration with RHEL AI and OpenShift AI products.

Vanguard in Oak Grove seeks ML Engineers with 8+ years experience and minimum $130,000+ compensation (salary not disclosed), requiring proficiency in Python (PySpark, PySQL) and 3+ years hands-on experience designing ETL pipelines using AWS services like Glue and SageMaker.

Cloud Infrastructure and MLOps

S&P Global in Raleigh offers $108,000-$215,000 for Lead ML Engineers focusing on generative AI solutions, requiring 8+ years progressive experience with 5+ years in production-level scalable code development. They emphasize containerization, cloud platforms, CI/CD, and workflow orchestration for large-scale distributed systems.

Formation Bio provides $180,000-$230,000 for Senior ML Engineers in their AI Foundations team, requiring 5+ years biotech/pharma software development experience with expertise in AI/ML frameworks (TensorFlow, PyTorch, LangChain, RAGAs) and cloud infrastructure deployment.

NTT DATA in Cleveland seeks AI/ML Engineers with 5+ years Python experience and 3+ years MLOps experience, focusing on generative AI platform capabilities on enterprise on-premise and cloud platforms (GCP-Vertex AI, Azure ML).

Specialized Domain Applications

Biotechnology and Healthcare

Syngenta represents the cutting edge of agricultural biotechnology, requiring candidates to work with trait research scientists and breeders to develop AI/ML models for biotech pipelines. They emphasize knowledge graphs for native traits and trait x genome interactions, requiring proven expertise in biological research applications.

Formation Bio focuses on pharmaceutical AI applications, requiring Master’s degree or higher in Computer Science, Engineering, AI, or Machine Learning. They seek candidates passionate about applying technology to drug development, working collaboratively with Product, Engineering, and Data Science teams.

Financial Services and Analytics

Vanguard combines ML with financial product development, requiring familiarity with Feature Store usage, LLMs, GenAI, RAG, and Prompt Engineering. They emphasize building scalable AI/ML solutions for predictive modeling in financial services environments.

Crunchbase in Carolina Beach offers $175,000-$195,000 for Senior ML Engineers developing sophisticated algorithms for private company intelligence, requiring 4+ years ML engineering experience with strong background in end-to-end production solutions.

Enterprise Software and Consulting

Red Hat’s open-source focus requires candidates who can contribute to PyTorch upstream community while integrating solutions into enterprise products. They emphasize collaborative development within AI Engineering teams and adherence to architectural design principles.

S&P Global seeks leaders who can architect production-grade generative AI services, requiring experience with large-scale distributed systems including infrastructure, data ingestion platforms, and microservices orchestration.

Advanced Technology Specializations

Generative AI and LLMs

Primesoft Consulting in Charlotte emphasizes optimization of gradient descent methods using LoRA (Low-Rank Adaptation) and Quantization, working on Retrieval-Augmented Generation (RAG) implementations for AI-driven applications.

Robert E Mason & Associates in Charlotte seeks AI Engineers for lightweight, domain-specific AI tools including embedded LLM agents and RAG systems, offering comprehensive benefits with focus on DOE-compliant environments requiring security clearances.

Production-Scale Deployment

Alldus requires minimum 2 years ML engineering experience with Python backend development and AWS model deployment, emphasizing real-time ML solution deployment and high-throughput system management.

Randstad in Charlotte offers $65-$75/hour contractor positions for ML Data Engineers with 4+ years experience, focusing on scalable data pipelines supporting development and deployment of ML models and applications.

Education and Experience Requirements

Advanced Degrees Emphasized

• Syngenta: PhD required in Bioinformatics, Computer Science, or Data Science with biology focus
• Formation Bio: Master’s degree or higher in Computer Science, Engineering, AI, or Machine Learning
• S&P Global: Bachelor’s degree in Computer Science or Engineering required
• Red Hat: Experience contributing to open source projects emphasized over specific degree requirements

Experience Level Variations

• Entry Level: Robert E Mason accepts 3+ years experience, academic experience acceptable
• Mid-Level: Vanguard, Formation Bio require 5+ years production experience
• Senior Level: S&P Global, Red Hat seek 8+ years with leadership capabilities
• Leadership Roles: S&P Global requires candidates who can lead engineering activities and collaborate across teams

Cross-Disciplinary Integration

Healthcare and Life Sciences

Formation Bio represents the intersection of AI and pharmaceutical development, requiring understanding of drug discovery processes alongside traditional ML skills. Syngenta combines ML with agricultural biotechnology, requiring knowledge of plant genomics and trait development.

Financial Technology

Vanguard emphasizes applying ML to financial services, requiring understanding of regulatory environments and financial product development. Crunchbase focuses on private company intelligence, combining business analytics with ML algorithm development.

Enterprise Systems Integration

Red Hat demonstrates the integration of ML with enterprise software systems, requiring understanding of containerization, distributed systems, and open-source development methodologies.

Industrial and Government Applications

Robert E Mason & Associates offers unique opportunities in DOE-compliant environments, requiring security clearances and understanding of highly regulated industrial systems including SCADA, DCS, and control systems.

Compensation Analysis by Role Type

Senior Individual Contributor Roles:

• Red Hat: $170,770-$312,730 (Senior/Principal ML Engineer)
• Formation Bio: $180,000-$230,000 (Senior ML Engineer I)
• Crunchbase: $175,000-$195,000 (Senior ML Engineer)

Leadership and Specialized Positions:

• S&P Global: $108,000-$215,000 (Lead ML Engineer)
• Vanguard: $130,000+ (ML Engineer, Specialist)

Contract and Consulting Roles:

• Randstad: $65-$75/hour (ML Data Engineer)
• Primesoft: Contractor rates (ML Engineer)

Key Industry Trends

Production-First Mentality: North Carolina employers consistently emphasize production deployment experience. S&P Global specifically seeks candidates who can “architect, build, and deploy production-grade generative AI services,” while Formation Bio requires experience “launching and scaling innovative 0-1 products.”

Open Source Contribution: Red Hat’s emphasis on PyTorch upstream contributions reflects North Carolina’s growing role in open-source AI development, requiring candidates who can contribute to community-driven projects.

Regulatory Compliance: Multiple employers emphasize experience in regulated environments, from Vanguard’s financial services compliance to Robert E Mason’s DOE requirements, reflecting North Carolina’s significant government and defense contractor presence.

Cross-Functional Leadership: Senior roles increasingly require both technical excellence and collaboration capabilities. Formation Bio emphasizes “strong collaboration & communication skills,” while S&P Global requires experience working “closely with world-class AI and ML teams.”

Remote Work Flexibility: Most positions offer hybrid or remote work options, with companies like Crunchbase operating “remote-first” policies, acknowledging North Carolina’s position as a talent hub serving national markets.

The North Carolina ML market offers diverse opportunities for graduates with machine learning master’s degrees, particularly those who can demonstrate practical production experience, open-source contributions, and the ability to apply ML solutions within specialized domains. The state’s combination of research institutions, established corporations, and emerging biotech companies creates a rich ecosystem for ML professionals seeking both technical challenges and meaningful impact.