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Founding Machine Learning Engineer Jobs in Hampton, 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 ...

Showing results 41-60

Founding Machine Learning Engineer information

See Hampton, VA salary details

$30.4K

$124.4K

$187K

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

As of Aug 21, 2026, the average yearly pay for founding machine learning engineer in Hampton, VA is $124,447.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,100.00 and $149,800.00 per year, depending on experience, location, and employer.

What is a founding machine learning engineer?

A Founding Machine Learning Engineer is one of the first technical team members at a startup who specializes in designing, building, and deploying machine learning systems. This role involves working closely with the founders to set the technical direction, build core AI products, and establish best practices for data and model development. In addition to hands-on coding and experimentation, a Founding Machine Learning Engineer often influences product decisions and helps shape the company's engineering culture. The role typically requires a blend of deep technical expertise, startup agility, and a willingness to tackle both high-level strategy and low-level engineering tasks.

What are some unique challenges and expectations for a founding machine learning engineer in an early-stage startup?

As a Founding Machine Learning Engineer, you'll face the unique challenge of building the company's machine learning infrastructure from the ground up, often with limited resources and rapidly evolving requirements. You'll be expected to wear many hats, from designing and deploying models to setting up data pipelines and collaborating closely with product and engineering teams. Your role will also involve making critical decisions about technology stacks and best practices that will shape the company's technical direction. Additionally, you'll have significant influence on the company's culture and have ample opportunities for growth as the team expands.

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

To thrive as a Founding Machine Learning Engineer, you need deep expertise in machine learning algorithms, software engineering, and data science, often supported by a degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow or PyTorch, cloud platforms, and experience deploying ML models in production are typically required. Strong problem-solving abilities, entrepreneurial mindset, and excellent communication skills set standout candidates apart. These skills and qualities are vital for driving innovation, building scalable solutions from scratch, and collaborating within a fast-paced startup environment.

Are founding machine learning engineers still in demand?

Founding machine learning engineers remain in high demand as companies seek to develop AI-driven products and services. They often require strong skills in deep learning, data modeling, and proficiency with tools like TensorFlow or PyTorch, with demand driven by growth in AI applications across industries.

How much does a founding machine learning engineer make?

A founding machine learning engineer typically earns between $100,000 and $180,000 annually, depending on experience, location, and company size. Equity and bonuses may also be part of the compensation package, especially in startup environments where they play a significant role in total earnings.

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

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

What job categories do people searching Founding Machine Learning Engineer jobs in Hampton, VA look for?

The top searched job categories for Founding Machine Learning Engineer jobs in Hampton, VA are:

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

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

Infographic showing various Founding Machine Learning Engineer job openings in Hampton, VA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $124,447 per year, or $59.8 per hour.

Data Scientist / AI Engineer

Ironclad Defense Works

Norfolk, VA โ€ข On-site

Full-time

Medical, Dental, Retirement, PTO

This job post hasย expired today.ย Applications are no longer accepted.


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
  • Bachelor’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.
  • Hands-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 fine-tuning and deployment of LLMs in secure, scalable environments.
  • Experience with machine learning frameworks such as TensorFlow, PyTorch, scikit-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 real-time streaming solutions.
  • Familiarity with Apache Airflow, Kafka, Spark, or comparable data-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 non-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 decision-making procedures.
  • Experience supporting military, defense, government, or international organizations.
  • Experience developing AI or data-engineering solutions using open-source frameworks and publicly available datasets.
  • Familiarity with military staff workflows and operational planning processes.
  • Experience with federated learning and privacy-preserving collaboration across multiple organizations or nations.
  • Experience supporting cross-domain data sharing and API-driven interoperability.
  • Familiarity with agile project-management methods and tools such as JIRA, Trello, or Microsoft Loop.
  • Experience briefing senior leaders and presenting actionable, data-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 mission-focused AI capabilities while working alongside military, civilian, and technical stakeholders across the NATO enterprise.
Clearance
This position requires an active 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 full-time employees may also receive a comprehensive benefits package, including medical and dental insurance, retirement benefits, paid leave, and professional development opportunities. 
How to Apply
Email your resume to jobs@idw.inc with the subject line: Data Scientist / AI Engineer
- (Your Name) Application" or respond to this job posting via the included web application.
Ironclad Defense Works is an Equal Opportunity Employer.
 

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