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Machine Learning Engineer Associate Jobs in North Carolina

The Hartford

Sr AI Machine Learning Engineer

Charlotte, NC · Hybrid

$117K - $175K/yr

The Hartford is seeking Senior AI Machine Learning Engineer to build Machine Learning Operations (MLOps) services for the Global Specialty Applied AI team. The Hartford is developing industryleading ...

RELX

Principal Machine Learning Engineer I

Raleigh, NC

$136K - $252K/yr

We are seeking a Principal Machine Learning Engineer to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products.

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All JobsMachine Learning Engineer Associate JobsMachine Learning Engineer Associate Jobs in North Carolina

Machine Learning Engineer Associate information

See North Carolina salary details

$37.7K

$75.1K

$120K

How much do machine learning engineer associate jobs pay per year?

As of Jun 27, 2026, the average yearly pay for machine learning engineer associate in North Carolina is $75,100.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,500.00 and $86,300.00 per year, depending on experience, location, and employer.

What are some common challenges faced by Machine Learning Engineer Associates when deploying models to production?

Machine Learning Engineer Associates often encounter challenges such as ensuring model scalability, managing data pipeline reliability, and addressing issues with model drift after deployment. Collaborating closely with data engineers and software developers is essential to integrate models seamlessly into existing systems. Additionally, balancing model performance with resource constraints and maintaining clear documentation for reproducibility are important aspects of the role. Gaining familiarity with deployment tools and best practices can help overcome these hurdles.

What are Machine Learning Engineer Associates?

Machine Learning Engineer Associates are entry-level professionals who help design, build, and maintain machine learning models and systems. They typically work under the guidance of senior engineers, assisting in data preprocessing, model training, and testing. Their responsibilities may include implementing algorithms, evaluating model performance, and deploying solutions to production environments. This role requires a strong foundation in programming, statistics, and machine learning principles, often acquired through education or internships.

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

To thrive as a Machine Learning Engineer Associate, you need a solid understanding of programming (especially Python), mathematics, and foundational machine learning concepts, typically supported by a relevant degree or coursework. Familiarity with tools and frameworks like TensorFlow, PyTorch, scikit-learn, and experience with version control systems such as Git are essential. Strong problem-solving abilities, communication skills, and a collaborative mindset help you work effectively within technical teams. These competencies ensure you can develop, implement, and improve machine learning models that deliver actionable insights and drive business value.
What are the most commonly searched types of Machine Learning Engineer jobs in North Carolina? The most popular types of Machine Learning Engineer jobs in North Carolina are:
What are popular job titles related to Machine Learning Engineer Associate jobs in North Carolina? For Machine Learning Engineer Associate jobs in North Carolina, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Associate jobs in North Carolina look for? The top searched job categories for Machine Learning Engineer Associate jobs in North Carolina are:
What cities in North Carolina are hiring for Machine Learning Engineer Associate jobs? Cities in North Carolina with the most Machine Learning Engineer Associate job openings:
Machine Learning Engineer Associate jobs near you
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Western Governors University

Raleigh, NC • On-site

$157K - $243K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 29 days ago

Western Governors University rating

8.6

Company rating: 8.6 out of 10

Based on 41 frontline employees who took The Breakroom Quiz

54th of 541 rated colleges and universities

Job description

If you're passionate about building a better future for individuals, communities, and our country-and you're committed to working hard to play your part in building that future-consider WGU as the next step in your career.

Driven by a mission to expand access to higher education through online, competency-based degree programs, WGU is also committed to being a great place to work for a diverse workforce of student-focused professionals. The university has pioneered a new way to learn in the 21st century, one that has received praise from academic, industry, government, and media leaders. Whatever your role, working for WGU gives you a part to play in helping students graduate, creating a better tomorrow for themselves and their families.

The salary range for this position takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs.

At WGU, it is not typical for an individual to be hired at or near the top of the range for their position, and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is:

Grade: Technical 411Pay Range: $157,000.00 - $243,400.00

Job Description

The Senior ML Engineer builds and deploys state-of-the-art NLP/LLM models at scale in a cloud environment, with a focus on improving student learning experiences. You lead by example, mentor junior engineers, and collaborate across cross-functional teams. You actively research the latest NLP/LLM techniques and translate them into practical, scalable solutions for the education domain. You communicate clearly with leadership and peers, influence product directions, and drive innovation that challenges the status quo.

Key Responsibilities

  • Strategic leadership

  • Define NLP initiatives, roadmaps, and success metrics in collaboration with the MLE manager.

  • Champion best practices in ML, data governance, and security within the team and across the organization.

  • Mentor junior engineers and serve as a technicalleadon complex ML projects.

  • Model research, development, and deployment

  • Research and prototypestate-of-the-artNLP/LLMtechniques;evaluate and select approaches suitable for production.

  • Develop, train, fine-tune, andoptimizeproduction-grade NLP/LLM models.

  • Deploy models to production with emphasis on performance, scalability, reliability, and observability.

  • Data, pipelines, and collaboration

  • Partner with Data Engineering to build robust data processing pipelines and high-quality training/inference data.

  • Work withMLOpsto ensure scalable, reproducible deployment, monitoring, and model governance.

  • Collaborate with Software, Infrastructure, and Security teams to integrate ML solutions into the university ecosystem.

  • Product impact and stakeholder engagement

  • Translate business requirements into NLP capabilities; collaborate with product stakeholders tovalidateoutcomes.

  • Apply NLP insights to unstructured data sources (e.g., transcripts, emails, mentor notes) to inform learning experiences.

  • Continuous improvement and learning

  • Stay current with NLP/LLM, DL, and AI trends; proactively apply innovations to use cases.

  • Contribute to standards, guidelines, and documentation for ML practices.

  • Communicate status, risks, and progress to leadership and cross-functional teams.

Minimum Qualifications:

  • 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 development in a cloud environment.

  • 3+ years building large-scale ML/DL models, from POC to production.

  • Hands-on experience with one or more DL frameworks (e.g.,PyTorch, TensorFlow).

  • Experience with cloud data platforms (AWS, Azure, GCP) and data/ML tooling (e.g., Databricks,MLFlow,Streamlit).

  • Proficiencyin ETL, feature engineering, datavisualization.

  • Experience operating high-availability, fault-tolerant, scalable distributed systems withGitOpspractices (Terraform preferred).

  • Familiarity with stream processing (ksqlDB, Spark Streaming, Beam/Flink) and modern ML deployment patterns.

  • Strong programming skills in Python, Java/Scala, and/orGo;fluency in clean, maintainable code.

  • Excellent analytical, critical thinking, and problem-solving abilities.

  • Effective written and verbal communication; comfortable explaining technical concepts to non-experts and senior leadership.

  • Ability to thrive in a fast-paced, collaborative environment.

  • Experience guiding junior engineers and providing technical leadership.

Preferred Qualifications

  • PhD in a related field.

  • Experience with Databricks and a broad range of ML tooling.

Equivalents and Substitutions

  • Equivalent relevant experience may substitute for degree requirements (1 year of experience per year of education at the discretion of the Hiring Manager).

#LI-GB1

Position & Application Details

Full-Time Regular Positions (classified as regular and working 40 standard weekly hours): This is a full-time, regular position (classified for 40 standard weekly hours) that is eligible for bonuses; medical, dental, vision, telehealth and mental healthcare; health savings account and flexible spending account; basic and voluntary life insurance; disability coverage; accident, critical illness and hospital indemnity supplemental coverages; legal and identity theft coverage; retirement savings plan; wellbeing program; discounted WGU tuition; and flexible paid time off for rest and relaxation with no need for accrual, flexible paid sick time with no need for accrual, 11 paid holidays, and other paid leaves, including up to 12 weeks of parental leave.

How to Apply: If interested, an application will need to be submitted online. Internal WGU employees will need to apply through the internal job board in Workday.

Additional Information

Disclaimer: The job posting highlights the most critical responsibilities and requirements of the job. It's not all-inclusive.

Accommodations: Applicants with disabilities who require assistance or accommodation during the application or interview process should contact our Talent Acquisition team at recruiting@wgu.edu.

Equal Employment Opportunity: All qualified applicants will receive consideration for employment without regard to any protected characteristic as required by law.

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