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Machine Learning Engineer Jobs in Greenville, NC

Machine Operator

Kinston, NC · On-site

$15.75 - $19/hr

... learning courses focusing on ways to develop your employability, certifications, career path; as ... sketches, and engineering specifications; determines sequence of operations, number of cuts ...

Machine Operator

Kinston, NC

$15.75 - $19/hr

... learning courses focusing on ways to develop your employability, certifications, career path; as ... sketches, and engineering specifications; determines sequence of operations, number of cuts ...

Machine Operator

Kinston, NC · On-site

$13.25 - $15.75/hr

... learning courses focusing on ways to develop your employability, certifications, career path; as ... sketches, and engineering specifications; determines sequence of operations, number of cuts ...

Machine Operator

Kinston, NC

$15.75 - $19/hr

... learning courses focusing on ways to develop your employability, certifications, career path; as ... Interprets blueprints, sketches, and engineering specifications; determines sequence of operations ...

... learning courses focusing on ways to develop your employability, certifications, career path; as ... Your Challenges Specify industrial jigs, tools and machinery for the industrial evolution: 35%

... learning courses focusing on ways to develop your employability, certifications, career path; as ... Your Challenges Specify industrial jigs, tools and machinery for the industrial evolution: 35%

Startup Engineer

Kinston, NC · On-site

$34 - $43/hr

Strong fundamental understanding of electrical design practices, machine/motion control systems, electro-mechanical systems, robotics, programming, and system integration * Understanding of PLC ...

Valicy is a company that creates games and the machines they run on. They are seeking a Gameplay ... learning and applying new tools. • Ability to make clear technical decisions with incomplete ...

Startup Engineer

Kinston, NC · On-site

$34 - $43/hr

Strong fundamental understanding of electrical design practices, machine/motion control systems, electro-mechanical systems, robotics, programming, and system integration * Understanding of PLC ...

Reliability Engineer

Kinston, NC

$95K - $120K/yr

The assets include mechanical and electrical CNC machinery, conventional production machinery, Jigs ... learning courses focusing on ways to develop your employability, certifications, career path; as ...

Reliability Engineer

Kinston, NC · On-site

$95K - $120K/yr

The assets include mechanical and electrical CNC machinery, conventional production machinery, Jigs ... learning courses focusing on ways to develop your employability, certifications, career path; as ...

Industrial Engineer - Composite

Kinston, NC · On-site

$84K - $111K/yr

... learning courses focusing on ways to develop your employability, certifications, career path; as ... Write specifications for Composite manufacturing machines and environment with the support of the ...

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Showing results 1-20

Machine Learning Engineer information

See Greenville, NC salary details

$30.2K

$123.4K

$185.4K

How much do machine learning engineer jobs pay per year?

As of Aug 30, 2026, the average yearly pay for machine learning engineer in Greenville, NC is $123,363.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,200.00 and $148,500.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What job categories do people searching Machine Learning Engineer jobs in Greenville, NC look for?

The top searched job categories for Machine Learning Engineer jobs in Greenville, NC are:

What cities near Greenville, NC are hiring for Machine Learning Engineer jobs?

Cities near Greenville, NC with the most Machine Learning Engineer job openings:

Infographic showing various Machine Learning Engineer job openings in Greenville, NC as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 28% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $115,139 per year, or $55.4 per hour.

Summer 2027 Intern - Machine Learning Engineering

Greenville, NC • On-site


Workiva
Software Development • 1 - 5K employees

9.9

Company rating: 9.9 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

1st of 246 rated software companies

Great coworkers

People enjoy working here

Good employer


$40/hr

Other

Retirement

Posted 2 days ago

New


Job description

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the development, deployment, and monitoring of machine learning models. Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management and Analytics organization. This is an excellent opportunity to gain hands-on experience in the machine learning lifecycle.

What You'll Do

  • Participate in discovery, requirements gathering, and prototyping of new tools and libraries
  • Implement tooling and features to support machine learning model development and deployment under the direction of a full-time Machine Learning Engineer
  • Help integrate tools such as LlamaIndex and LlamaParse into existing workflows
  • Assist in building and deploying AI Agents to automate data processing and analysis tasks
  • Participate in code reviews
  • Implement and update tests (unit, integration)
  • Track tasks and complete status updates using internal tools
  • Work in an Agile development methodology alongside your teammates

What You'll Need

Minimum Qualifications

  • Currently pursuing a bachelor’s degree or higher in Statistics, Mathematics, Computer Science, Physics, Electrical Engineering, or related field of study
  • Possess solid programming skills
  • Basic experience with source control systems such as Git

Preferred Qualifications

  • Work effectively within a geographically distributed team
  • Demonstrate strong communication and organizational skills
  • Familiarity with the data science lifecycle and basic machine learning concepts
  • Experience with containerization tools such as Docker and Kubernetes
  • Knowledge of cloud platforms such as AWS
  • Proficiency with Python and/or Go
  • Familiarity with REST APIs

Travel Requirements & Working Conditions

  • Minimal travel
  • Reliable internet access for any period of time working remotely, not in a Workiva office

Location: This internship is primarily a remote opportunity. However, if you are located near one of our office hubs, you are welcome to work in a hybrid capacity and utilize our office spaces. Check out our article on Workplace Flexibility to learn more.

When can you expect to hear back?

We are committed to attending all career fairs and recruitment events before closing our positions. That means, this position might be open without updates for a few weeks to give us time to connect with all potential candidates before wrapping up the recruitment season. Check out our tentative timeline below to see when you can expect to hear from us!

Postings close: September 27, 2026

Engineering postings close: October 2, 2026

Interviews: Early to mid October

Offers: Late October

2027 Start Dates:

This position has opportunities to start in the Spring or Summer. Please see our start dates below and let us know your availability in your application.

  • Spring 2027 Internships: Monday, January 4, 2027 (15-20 hours per week max)
  • Summer 2027 Internships: Monday, May 17, 2027 (40/hours per week max)

How You’ll Be Rewarded

Salary range in the US: $40.00 - $40.00 401(k) participation and match

Paid sick leave

A unique opportunity to further your learning experience through additional internship seasons

Why Join Workiva

Workiva is the platform designed to bring confidence, control, and a competitive edge to the world’s most complex organizations. Our AI-powered platform unifies finance, risk, and sustainability on a single, secure foundation-ensuring data is trusted, traceable, and ready to act on. With an unbroken path from source to output, leaders gain confidence in their numbers, visibility into current and emerging risks, and the ability to move with speed and precision in a constantly changing world.

At Workiva, you’ll bring technology to market that executives, boards, and regulators depend on. The work you do here helps organizations navigate uncertainty, maintain trust, and make decisions that stand up to scrutiny. If you’re energized by meaningful challenges, inspired by collaborative teams, and motivated to help organizations turn uncertainty into advantage, we’d love to meet you.

Employment decisions are made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other protected characteristic.

Workiva is committed to working with and providing reasonable accommodations to applicants with disabilities. To request assistance with the application process, please email earlycareer@workiva.com .

Workiva employees are required to undergo comprehensive security and privacy training tailored to their roles, ensuring adherence to company policies and regulatory standards.

Workiva supports employees in working where they work best - either from an office or remotely from any location within their country of employment.



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