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

Provide effective challenge to model owners and developers by identifying risks, limitations, and ... Baseline familiarity with AI or machine learning concepts and related governance considerations.

Linear Algebra Tutor

Wilmington, NC · Remote

$18 - $40/hr

... data science, engineering, and advanced mathematics. * Conceptual Teaching & Problem-Solving ... machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive Instruction:

Engineers provide 24-hour response to machinery and system issues and oversee the operation, maintenance, and troubleshooting of all vessel equipment, including pumps, motors, engines, electrical and ...

Engineers provide 24-hour response to machinery and system issues and oversee the operation, maintenance, and troubleshooting of all vessel equipment, including pumps, motors, engines, electrical and ...

Sr Development Engineer

Wilmington, NC · On-site

$101K - $139K/yr

... rate, machine utilization, product quality, new product quality, environmental compliance, raw ... S. degree in mechanical engineering, Materials Science or similar technical field (e.g. physics ...

Sr Development Engineer

Wilmington, NC · On-site

$101K - $139K/yr

... rate, machine utilization, product quality, new product quality, environmental compliance, raw ... S. degree in mechanical engineering, Materials Science or similar technical field (e.g. physics ...

Sr Development Engineer

Wilmington, NC · On-site

$101K - $139K/yr

Collaborating with other equipment/machine design experts within and outside of OFC development ... S. degree in mechanical engineering, Materials Science or similar technical field (e.g. physics ...

Showing results 21-40

Machine Learning Engineer information

See Leland, NC salary details

$27.2K

$111.3K

$167.3K

How much do machine learning engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for machine learning engineer in Leland, NC is $111,302.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,700.00 and $134,000.00 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 are the most commonly searched types of Machine Learning Engineer jobs in Leland, NC?

The most popular types of Machine Learning Engineer jobs in Leland, NC are:

What are popular job titles related to Machine Learning Engineer jobs in Leland, NC?

For Machine Learning Engineer jobs in Leland, NC, the most frequently searched job titles are:

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

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

Infographic showing various Machine Learning Engineer job openings in Leland, NC as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 25% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $111,302 per year, or $53.5 per hour.

Model Risk Analyst

Wilmington, NC • On-site

Full-time

Posted 5 days ago


Job description

About Us

Live Oak Bank is a digital bank that serves small business owners across the country. Our groundbreaking spin on service and technology has fueled our mission to be America's Small Business Bank. Our products help customers buy, build, and expand their business, and our high-yield savings and CD products help them grow their hard-earned money. At Live Oak, we never lose sight of the well-being of our people. We believe our employees are the heart of our company. Our commitment to our customers and culture is intertwined, and we seek those who embody and embrace what it takes to empower the American dream.

How This Role Impacts Live Oak and Its People

As a Model Risk Analyst, you help ensure Live Oak's models and AI-enabled solutions are sound, well-governed, and aligned with business objectives and regulatory expectations. Working within the second line of defense, you provide independent review, effective challenge, and ongoing oversight across the full model and AI lifecycle. Your work supports safe and sound operations and informed decision-making across the model and AI lifecycle.

Location: Required to be location in North Carolina market. Work Sponsorship is not supported now or in the future.

What You'll Do at Live Oak

Model Validation & Effective Challenge

  • Conduct quantitative and qualitative validations of internally developed and vendor-provided models, assessing conceptual soundness, data, assumptions, methodology, outcomes, and limitations.

  • Review and challenge ongoing monitoring results to confirm models continue to perform as intended, and escalate emerging risks.

  • Assess model change requests, including methodology changes, data updates, and enhancements, and help determine the appropriate level of review.

  • Provide effective challenge to model owners and developers by identifying risks, limitations, and control gaps, and recommending remediation.

  • Document findings, assign criticality, and track remediation through to closure.

AI Governance & Emerging Technology

  • Test, evaluate, and independently review AI-enabled tools, agents, and skills to confirm alignment with governance standards, regulatory expectations, and business objectives.

  • Assess key AI-specific risks such as bias, data privacy, and reliability, and support monitoring practices for AI-enabled tools and systems.

  • Monitor emerging AI tools and industry trends to help flag governance and risk considerations early as new use cases are adopted.

Analysis & Reporting

  • Analyze quantitative and qualitative data to identify trends, anomalies, performance concerns, and emerging risks affecting model effectiveness and decision-making.

  • Produce clear, well-structured validation, monitoring, and analytical documentation that communicates technical findings to technical and non-technical audiences.

  • Support development of risk dashboards, key risk indicators, and executive reporting.

Governance, Framework & Stakeholder Support

  • Support the model and AI governance framework by handling intake reviews, risk tiering, validation scheduling, and findings tracking, and by maintaining the model and AI inventory.

  • Contribute to governance materials and reporting for committees such as the Model Risk Committee and AI Governance Forum.

  • Maintain a current understanding of model risk governance, policies, procedures, and regulatory guidance, including SR 26-2 and emerging AI/ML governance expectations.

Required Experience

  • Bachelor's degree in Statistics, Mathematics, Economics, Finance, Engineering, Data Analytics, Computer Science, or a related quantitative field.

  • 2-4 years of experience in model risk management, model validation, model development, quantitative analytics, or a related risk management function within financial services.

  • Experience reviewing or validating quantitative and/or qualitative models, such as credit risk, allowance, forecasting, pricing, BSA/AML, or operational models.

  • Ability to analyze model documentation, data, assumptions, methodologies, and results, and to apply independent judgment and effective challenge.

  • Baseline familiarity with AI or machine learning concepts and related governance considerations.

  • Proficiency with Python and SQL, and hands-on experience with version-control and analytical platforms such as GitHub and Databricks.

  • Strong written and verbal communication skills, able to convey complex concepts to varied audiences.

  • Well-organized and self-directed, with intellectual curiosity and a proactive, collaborative approach to managing competing priorities.

Preferred Experience

  • Advanced degree (Master's) in a quantitative discipline.

  • Knowledge of banking products, financial services, and model risk management practices.

  • Experience evaluating AI, machine learning, or agentic/LLM-based systems and their governance considerations.

  • Familiarity with AI governance frameworks such as the NIST AI Risk Management Framework or emerging interagency guidance.

  • Experience with additional analytical tools such as R or SAS.

  • Experience developing risk dashboards, key risk indicators, and executive reporting.

Our Values

  • Dedication:Possess a deep commitment to Live Oak Bank's mission and core values, exemplified through a strong work ethic, adaptability and pride in your work.

  • Ownership:Take initiative to deliver positive results by proactively and creatively solving problems, while maintaining a high degree of quality.

  • Respect:Treat everyone with courtesy, politeness, and kindness.

  • Innovation:Embrace fresh ideas and fearlessly contribute new solutions to emerging or existing problems.

  • Teamwork: Foster collaboration, accountability, and trust with others and understand that together, we do more

For a detailed overview of our employee benefits please visit:http://www.liveoakbank.com/careers/

Live Oak Bank is an Affirmative Action and Equal Opportunity Employer, Minorities/Women/Veterans/Disabled. We consider applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, genetic information, veteran status or disability. Equal access to programs, service and employment is available to all persons. Those applicants requiring reasonable accommodation to the application and/or interview process should notify human resources atHumanResources@liveoak.bank.

EEO is the Law

The base pay range for this position is $82,240.00 - $133,640.00 per year. Compensation may also include annual bonuses and long-term incentives, subject to various metrics and company policy. A candidate's salary is determined by several factors including travel, relevant work experience or skills and expertise.

Please note that we provide at least the minimum requirement of paid sick leave to our employees who reside in states that require employer-paid sick leave, including but not limited to Arizona, California, Colorado, District of Columbia, Maine, Maryland, Massachusetts, Michigan, Nevada, New Jersey, New Mexico, New York, Oregon, Rhode Island, Vermont, and Washington.