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Machine Learning Engineer Jobs in Matthews, NC (NOW HIRING)

Varsity Tutors

Machine Learning Tutor

Charlotte, NC · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Matthews, NC · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

CRC Group

Software Engineer - Machine Learning

Charlotte, NC · On-site

$95K - $130K/yr

... the machine learning function at a market-leading insurance company. As one of the first data ... Leverage continuous engineering practices to deliver business value regarding effectiveness of the ...

Tihinsurance

Software Engineer - Machine Learning

Charlotte, NC · On-site

$95K - $130K/yr

... the machine learning function at a market-leading insurance company. As one of the first data ... Leverage continuous engineering practices to deliver business value regarding effectiveness of the ...

Corning

Machine Vision Engineer II

Concord, NC

$82K - $112K/yr

Use imaging and machine learning tools to automate manufacturing processes * Partner with engineering, operations, and process teams to solve plant challenges * Analyze process data and apply ...

Deloitte

AI Solutions Architect

Charlotte, NC · On-site

$61.50 - $81/hr

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

Deloitte

Senior AI Engineer - SFL Scientific

Charlotte, NC · On-site

$102K - $140K/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 ...

Staffingine LLC

MLOps Engineer

Charlotte, NC · On-site

Overall 8 to 10 years of solid experience in the areas of data engineering machine learning data science * 4 to 6 years of strong experience with the following machine learning topics classification ...

Marencor

ML Engineer

Charlotte, NC · On-site

Proven experience in data science, machine learning, or predictive analytics roles * Proficiency in programming languages commonly used in data science (e.g., Python, R, etc.) * Experienced in using ...

Donato Technologies, Inc

ML Ops Engineer

Charlotte, NC · On-site

$60/hr

Overview Machine Learning AI team seeking a ML Ops Engineer to drive the full lifecycle of machine learning solutions. Key Responsibilities * Develop and maintain ML pipelines using tools like MLflow ...

CDW

Senior ML, MLOps Engineer

Concord, NC · On-site

$97K - $133K/yr

The Senior ML / MLOps Engineer designs, builds, and operates scalable machine learning solutions on the Databricks platform. This role partners closely with data scientists and analytics teams to ...

Scout Motors

Lead, AI Engineering

Charlotte, NC

$100K - $131K/yr

The team combines expertise in machine learning, generative AI, data engineering, and platform infrastructure to deliver innovative solutions that improve business outcomes and accelerate digital ...

Tata Consultancy Services

AI/ML Engineer

Charlotte, NC · On-site

Tata Consultancy Services is seeking an AI/ML Engineer to design and develop AI agents and machine learning solutions. The role requires strong engineering skills and expertise in deploying AI ...

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Showing results 1-20

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Matthews, NC

Machine Learning Engineer information

See Matthews, NC salary details

$29.6K

$121K

$181.8K

How much do machine learning engineer jobs pay per year?

As of Jul 13, 2026, the average yearly pay for machine learning engineer in Matthews, NC is $121,013.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,400.00 and $145,700.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

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 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.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

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 engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

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.

More about Machine Learning Engineer jobs
What cities near Matthews, NC are hiring for Machine Learning Engineer jobs? Cities near Matthews, NC with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Matthews, NC as of July 2026, with employment types broken down into 94% Full Time, 3% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $121,013 per year, or $58.2 per hour.

SS Hackathon - AI Developer / AI Engineer

NEOGOV - Test

Concord, NC • On-site, Remote

Other

Medical, Dental, Vision, Retirement

Re-posted 28 days ago

Job description

Description Neogov is at the forefront of digital innovation, leveraging cutting-edge technology to solve complex problems and transform industries. We are seeking a talented AI Developer to join our dynamic team and help us create intelligent, scalable solutions that drive business impact. Example of Duties Develop AI Models: Design, build, train, and test machine learning (ML) and deep learning models to address specific business challenges, such as natural language processing (NLP), computer vision, or predictive analytics.

Data Handling: Collaborate with data scientists and engineers to collect, clean, preprocess, and analyze large datasets to ensure data quality and availability for model training. Integrate AI Solutions: Deploy AI models into production environments and seamlessly integrate them with existing systems, applications, and APIs. Optimize Performance: Monitor, evaluate, and fine-tune AI models and applications for performance, accuracy, and scalability.

Collaborate & Communicate: Work effectively within multidisciplinary teams, articulating complex technical concepts and findings to both technical and non-technical stakeholders. Research & Innovation: Stay updated with the latest advancements in AI technologies, tools, and industry trends to propose innovative solutions. Typical Qualifications Education:Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or a related quantitative field.

Experience:Proven experience as an AI Developer, Machine Learning Engineer, or similar role. Programming Proficiency:Strong coding skills in Python, Java, R, and/or C++. AI Frameworks:Hands-on experience with AI/ML frameworks and libraries such asTensorFlow,PyTorch, scikit-learn, or Keras.

Technical Knowledge:Solid understanding of machine learning algorithms, neural networks, data structures, and software architecture. Problem-Solving:Excellent analytical and problem-solving skills with attention to detail. Supplemental Information Experience with cloud computing platforms likeAWS, Google Cloud (GCP), or Azure for model deployment and scaling.

Familiarity with DevOps practices and MLOps tools (e.g., Docker, Kubernetes, MLflow). Knowledge of big data technologies such as Hadoop or Spark. Benefits Competitive salary and compensation package

Comprehensive health, dental, and vision insurance. [401(k) matching or retirement plan]. Flexible work environment/remote options.

Opportunities for continuous learning and professional development (e.g., conference sponsorships, training stipends).

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