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Machine Learning Engineer Opt Jobs in Dunn, NC (NOW HIRING)

DataAnnotation

QA Engineer - AI Trainer

Fayetteville, NC · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

DataAnnotation

Automated QA Engineer - AI Trainer

Cary, NC · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

Kanak Elite Services Inc

Data and AI Analyst

Cary, NC · On-site

AI & Machine Learning • Assist in building and monitoring AI models using SAS Viya and other ... data programming languages. • Understanding of ethical AI, data privacy, and public sector ...

Booz Allen Hamilton, Inc.

Data Engineer

Fayetteville, NC · On-site

$77K - $176K/yr

Rapid advances in IoT, machine learning, and artificial intelligence mean organizations have access ... As a senior Data Engineer at Booz Allen, you will design and build data platforms and pipelines ...

Q2 Software, Inc.

Data Engineer

Cary, NC · On-site

$106K - $127K/yr

... data engineering, cloud platforms, and distributed systems. A Typical Day: * Design, build, and ... Deliver clean, well-structured datasets to support fraud analytics, machine learning models, and ...

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All JobsMachine Learning Engineer Opt JobsMachine Learning Engineer Opt Jobs in Dunn, NC

Machine Learning Engineer Opt information

See Dunn, NC salary details

$27.3K

$111.6K

$167.6K

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

As of Jul 15, 2026, the average yearly pay for machine learning engineer opt in Dunn, NC is $111,561.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,900.00 and $134,300.00 per year, depending on experience, location, and employer.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

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

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

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 a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.
What job categories do people searching Machine Learning Engineer Opt jobs in Dunn, NC look for? The top searched job categories for Machine Learning Engineer Opt jobs in Dunn, NC are:
What cities near Dunn, NC are hiring for Machine Learning Engineer Opt jobs? Cities near Dunn, NC with the most Machine Learning Engineer Opt job openings:
Machine Learning Engineer Opt jobs near you
Data Science, AI & Analytics Lead

Data Science, AI & Analytics Lead

FORWARD EDGE AI, INC

Fayetteville, NC • On-site

Contractor

Posted 27 days ago

Job description

Data Science, AI & Analytics Lead
Location: Fort Bragg, NC
Work Arrangement: Hybrid (Must reside within 50 miles of Fort Bragg, NC)
Clearance: Active Secret Clearance Required
Employment Type: Full-Time
Position Overview
Forward Edge-AI is seeking a Data Science, AI & Analytics Lead to support the U.S. Army Reserve CIO/G-6. This position will lead enterprise data analytics, artificial intelligence, machine learning, visualization, and data governance initiatives that enable data-driven decision-making, operational readiness, and digital transformation across the Army Reserve enterprise.
The ideal candidate will provide technical leadership for advanced analytics programs, develop executive-level dashboards and reporting solutions, guide AI/ML implementation efforts, and ensure compliance with enterprise data governance and quality standards. This role requires the ability to communicate complex analytical findings to senior military and civilian leadership and translate data into actionable business insights.
Work Location Requirement
This is a hybrid position. Candidates must reside within 50 miles of Fort Bragg, NC and be available to work on-site as required to support meetings, stakeholder engagements, workshops, and Government-directed activities. Candidates must be able to obtain and maintain installation access.
Key Responsibilities
  • Lead the development and implementation of AI/ML models, predictive analytics, and advanced data science solutions
  • Design and deliver executive dashboards, reports, scorecards, and visualizations using Power BI and other approved analytics platforms
  • Analyze structured and unstructured data to support operational readiness, strategic planning, and executive decision-making
  • Oversee enterprise data integration, ETL processes, API development, and data engineering activities
  • Establish and maintain data governance frameworks, metadata standards, and data quality controls
  • Identify authoritative data sources and ensure compliance with Army and DoD data strategies
  • Evaluate emerging technologies and recommend innovative solutions that support enterprise modernization initiatives
  • Brief senior military and civilian leadership on analytical findings, recommendations, and program performance
  • Collaborate with stakeholders, data engineers, analysts, and technical teams to deliver mission-focused solutions
  • Support Agile, DevSecOps, and modern data platform practices
  • Provide technical leadership and mentorship to analytics and data teams

Required Qualifications
  • Bachelor's or Master's degree in Data Science, Computer Science, Mathematics, or a related field
  • Minimum of five (5) years of experience in data science, analytics, AI/ML, business intelligence, or related disciplines
  • Experience developing predictive models, machine learning solutions, and advanced analytics products
  • Proficiency with Python, SQL, Power BI, Azure Machine Learning, Databricks, or similar analytics platforms
  • Experience with data integration, ETL development, and enterprise data management
  • Strong understanding of data governance, data quality, metadata management, and data stewardship
  • Experience supporting federal agencies, Department of Defense organizations, or large enterprise environments
  • Active Secret Security Clearance
  • U.S. Citizenship required
  • Ability to communicate complex technical concepts to executive and non-technical audiences

Preferred Qualifications
  • Experience supporting Army, DoD, or federal data and analytics programs
  • Experience with Army Vantage, Advana, Azure cloud environments, or similar enterprise platforms
  • Microsoft, Azure, AI/ML, Data Analytics, Agile, or Project Management certifications
  • Experience leading cross-functional technical teams
  • Experience briefing General Officer, Senior Executive Service, or executive-level stakeholders

Why Forward Edge-AI
At Forward Edge-AI, you will work alongside mission-focused professionals delivering cutting-edge AI, analytics, and data solutions that directly support national defense objectives. Join a team committed to innovation, collaboration, and advancing the future of data-driven decision-making across the Department of Defense.

Apply