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Machine Learning Engineer Jobs in Portsmouth, VA

HII's diverse workforce includes skilled tradespeople; artificial intelligence, machine learning (AI/ML) experts; engineers; technologists; scientists; logistics experts; and business administration ...

AI Engineer

Norfolk, VA ยท On-site

The AI Engineer will design, develop, and deploy machine learning, natural language processing, and generative AI solutions supporting the NMMES program at Naval Sea Systems Command (NAVSEA) in ...

AI Engineer

Norfolk, VA ยท On-site

The AI Engineer will design, develop, and deploy machine learning, natural language processing, and generative AI solutions supporting the NMMES program at Naval Sea Systems Command (NAVSEA) in ...

Research emerging AI, machine learning, and data engineering technologies and recommend innovative applications for customer missions. * Support technical documentation, architecture development ...

Data Scientist

Suffolk, VA ยท On-site

$77K - $176K/yr

You Have: * 2+ years of experience with artifi cia l intelligence, data science, machine learning engineering, sof tware engineering, data research, or data analytics * Experience with sof tware ...

Showing results 41-60

Machine Learning Engineer information

See Portsmouth, VA salary details

$30.5K

$124.7K

$187.3K

How much do machine learning engineer jobs pay per year?

As of Aug 18, 2026, the average yearly pay for machine learning engineer in Portsmouth, VA is $124,650.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,300.00 and $150,000.00 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 Portsmouth, VA?

The most popular types of Machine Learning Engineer jobs in Portsmouth, VA are:

What are popular job titles related to Machine Learning Engineer jobs in Portsmouth, VA?

For Machine Learning Engineer jobs in Portsmouth, VA, the most frequently searched job titles are:

What cities near Portsmouth, VA are hiring for Machine Learning Engineer jobs?

Cities near Portsmouth, VA with the most Machine Learning Engineer job openings:

Infographic showing various Machine Learning Engineer job openings in Portsmouth, VA as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 26% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $124,650 per year, or $59.9 per hour.

Data Scientist / AI Engineer

Ironclad Defense Works

Norfolk, VA โ€ข On-site

$115 - $130/hr

Other

Medical, Dental, Retirement, PTO

Posted 14 days ago


Job description

Data Scientist / AI Engineer

Location: Norfolk, Virginia

Employment Type: Full-time, On-site

Security Clearance: Active NATO or U.S. National SECRET clearance required

Citizenship: Must be a citizen of a NATO member nation

The Role

Ironclad is seeking an experienced Data Scientist / AI Engineer to support the development and implementation of advanced data science, artificial intelligence, and large language model capabilities within the NATO enterprise.

This position requires a technically versatile professional who can bridge data engineering, software development, machine learning, and operational mission requirements. The selected candidate will design scalable data architectures, build and optimize data pipelines, develop API-based infrastructure, and support the secure deployment of AI and machine learning solutions in cloud-based and hybrid environments.

The role requires strong hands-on experience with generative AI, large language models (LLMs), distributed systems, microservices, containerized applications, and modern software engineering practices. The successful candidate must also be able to translate complex operational challenges into practical technical solutions for military and civilian stakeholders.

Key Responsibilities
  • Develop and implement scalable data science and AI capabilities supporting NATO initiatives.
  • Design, build, and maintain data pipelines for structured and unstructured data.
  • Prepare, cleanse, transform, and optimize data for LLM training, fine-tuning, inference, and analytics.
  • Develop API-based infrastructure that integrates LLMs and machine learning models with operational systems.
  • Design and support microservices and containerized AI/ML applications.
  • Build distributed data storage and processing solutions using cloud-based or hybrid architectures.
  • Develop real-time data processing and streaming capabilities for operational decision support.
  • Automate data engineering processes and improve the scalability, efficiency, and reliability of AI infrastructure.
  • Implement monitoring, logging, traceability, and performance-optimization tools for data pipelines and APIs.
  • Support the secure deployment of AI and LLM solutions in Microsoft Azure, AWS, or comparable environments.
  • Develop tools that improve data accessibility for data scientists, analysts, engineers, and operational users.
  • Collaborate with data scientists, software engineers, system architects, and other technical stakeholders.
  • Support federated learning, cross-domain data sharing, and secure collaboration across NATO nations.
  • Develop proofs of concept for LLM-based and advanced analytics applications.
  • Evaluate operational requirements and recommend appropriate AI, software, and data-engineering solutions.
  • Create dashboards, reports, and visual analytics for senior and non-technical stakeholders.
  • Provide technical briefings, mentoring, and training in AI engineering, data science, API development, and digital literacy.
  • Research emerging developments in generative AI, distributed computing, data architecture, and software engineering.
  • Promote responsible, secure, and ethical AI practices throughout solution development and deployment.
Required Qualifications
  • Bachelorโ€™s degree or higher from a nationally recognized university in data science, data analytics, artificial intelligence, mathematics, physics, computer science, software engineering, or a closely related discipline.
  • At least four years of professional experience as a Data Scientist, Machine Learning Engineer, Data Engineer, Software Engineer, or in a closely related role.
  • Demonstrated experience developing operational AI or machine learning solutions.
  • Experience with distributed systems and cloud-based or hybrid architectures.
  • Experience designing API-based infrastructure and microservices architectures.
  • Handsโ€‘on experience developing and deploying containerized applications using technologies such as Docker or Kubernetes.
  • Demonstrated experience with generative AI and large language models.
  • Experience preprocessing data and supporting the fineโ€‘tuning and deployment of LLMs in secure, scalable environments.
  • Experience with machine learning frameworks such as TensorFlow, PyTorch, scikitโ€‘learn, or comparable technologies.
  • Strong programming experience with Python, Java, Scala, or similar languages.
  • Experience with version control, CI/CD pipelines, automated testing, and modern software engineering practices.
  • Experience building and optimizing ETL processes, data pipelines, and realโ€‘time streaming solutions.
  • Familiarity with Apache Airflow, Kafka, Spark, or comparable dataโ€‘engineering technologies.
  • Experience architecting or maintaining data lakes, data warehouses, distributed storage systems, or NoSQL solutions.
  • Knowledge of platforms such as Delta Lake, Snowflake, Hadoop, or comparable technologies.
  • Experience applying AI to operational decision support and the analysis of unstructured data, including text or imagery.
  • Strong understanding of data security, privacy, sovereignty, and responsible AI practices.
  • Experience developing dashboards, visual reports, and analytics using Tableau, Microsoft Power BI, Kibana, or comparable tools.
  • Ability to translate operational problems into practical AI and machine learning solutions.
  • Demonstrated success working with multidisciplinary technical teams.
  • Strong written and verbal communication skills.
  • Ability to explain technical concepts to nonโ€‘technical stakeholders and senior leaders.
  • Ability to mentor or train personnel in AI engineering, data science, or software development concepts.
Preferred Qualifications
  • Familiarity with NATO processes, organizational structures, operational culture, and decisionโ€‘making procedures.
  • Experience supporting military, defense, government, or international organizations.
  • Experience developing AI or dataโ€‘engineering solutions using openโ€‘source frameworks and publicly available datasets.
  • Familiarity with military staff workflows and operational planning processes.
  • Experience with federated learning and privacyโ€‘preserving collaboration across multiple organizations or nations.
  • Experience supporting crossโ€‘domain data sharing and APIโ€‘driven interoperability.
  • Familiarity with agile projectโ€‘management methods and tools such as JIRA, Trello, or Microsoft Loop.
  • Experience briefing senior leaders and presenting actionable, dataโ€‘driven recommendations.
  • Knowledge of ethical AI principles, including bias mitigation, responsible data handling, transparency, and secure deployment.
Why Join Ironclad

Ironclad supports complex defense and international missions by providing experienced professionals who combine technical expertise with an understanding of operational requirements. This position offers the opportunity to contribute directly to secure, scalable, and missionโ€‘focused AI capabilities while working alongside military, civilian, and technical stakeholders across the NATO enterprise.

Clearance

This position requires anactive NATO or National SECRET (or higher) security clearance. Applicants who do not possess the clearance specified above cannot be considered at this time.

Compensation

Compensation for this position ranges from $115,000 - $130,000 annually. Final salary will be based on factors such as experience, education, skills, qualifications, contract requirements, and overall affordability.

Eligible fullโ€‘time employees may also receive a comprehensive benefits package, including medical and dental insurance, retirement benefits, paid leave, and professional development opportunities.

Ironclad Defense Works is an Equal Opportunity Employer.

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