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About This Role
Date: Jul 27, 2026
Location: Virginia Beach, VA, Virginia, United States
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Company: HII's Mission Technologies division
Requisition Number: 29568
Required Travel: 0 \- 10%
Employment Type: Full Time/Salaried/Exempt
Anticipated Salary Range: $95,004\.00 \- $122,000\.00
Security Clearance: Secret
Level of Experience: Mid
This opportunity resides with Global Security (GS). Mission Technologies’ Global Security (GS) group comprises live, virtual, constructive (LVC) solutions; fleet sustainment; nuclear and environmental; and Australia business.
As a trusted partner to our military customers, HII designs, develops and operates the largest LVC enterprise that prepares warfighters for cross\-domain battle. With advanced technologies to enable mission readiness, HII understands that preparation requires full coordination—not readiness in piece\-parts.
For more than 40 years, the U.S. Navy has entrusted HII to maintain and modernize the vast majority of its fleet. With a holistic approach to life\-cycle maritime defense systems—from small watercraft to submarines, surface combatants and aircraft carriers—HII ensures a high state of readiness.
HII supports the Department of Energy’s national security mission through the management and operation of its sites, as well as the safe cleanup of legacy waste across the country. HII meets clients’ toughest nuclear and environmental challenges.
Leadership Mindset at HII – Mission Technologies
Leadership at HII is a mindset, not a title. Through our Leadership Capability Framework, we define how every employee grows, leads, and contributes—regardless of role. It sets the standard for how you can develop yourself and what you can expect from leaders across our organization. We look for candidates who want to grow in alignment with these capabilities:
Know \& Grow Your People – Commit to learning and supporting team success.
Build Relationships – Communicate openly, collaborate well, and build trust.
Take Ownership – Deliver on commitments and take pride in your work.
Customer First – Focus on the mission and those we serve.
Shape the Future – Bring ideas, curiosity, and continuous improvement.
Act with Urgency – Take initiative and follow through with purpose.
These capabilities guide how all employees contribute to our shared success across Mission Technologies.
Summary
HII Mission Technologies is seeking a Machine Learning Engineer to support the design, development, and deployment of advanced training and simulation capabilities within the Advanced Training Domain (ATD) System—a shipboard combat system trainer that enhances U.S. Navy operational readiness. This full‑time, on‑site role is part of a high‑performing engineering team delivering mission‑driven solutions that improve warfighter training and decision‑making.
In this role, you will help integrate machine‑learning and data‑driven capabilities that elevate the realism, adaptability, and performance of next‑generation combat system training environments.
Impact, Growth \& Development
Strengthen U.S. Navy readiness by engineering ML solutions that improve training fidelity and system performance
Collaborate with software engineers, data engineers, analysts, and end users to solve operationally relevant challenges
Grow your skills through hands‑on work with high‑fidelity simulation systems, real‑world training data, and modern ML/AI toolchains
Contribute to innovations that shape future combat system training platforms
Key Job Responsibilities
Participate in Agile sprint planning and execution across cross‑functional engineering teams
Design, develop, and deploy machine learning models supporting simulation accuracy, data analytics, performance prediction, and system‑behavior modeling
Build data pipelines for collection, preprocessing, labeling, and training using structured and unstructured Navy training data
Integrate ML models into Linux‑based training systems using containers, APIs, or embedded inference engines
Troubleshoot, optimize, and maintain ML workflows including performance tuning, error analysis, and model explainability
Develop supporting documentation such as architecture diagrams, data‑flow documentation, model cards, evaluation reports, and code commentary
Conduct developer testing in lab environments and aboard ship when required
Provide occasional on‑site support for installations, model validation, and user evaluations (up to 10% travel)
Perform additional related duties as assigned to support project and organizational needs
What you must have
Required Education \& Experience
2 years of relevant experience with a Bachelor’s degree in a related field, OR
0 years of experience with a Master’s degree in a related field, OR
High school diploma or equivalent and 6 years of relevant experience
Required Knowledge \& Skills
Experience developing and deploying machine learning models using Python frameworks such as PyTorch, TensorFlow, or Scikit‑learn
Hands‑on experience with Linux‑based development environments
Familiarity with Agile/Scrum methodologies
Experience implementing data pipelines, feature engineering, and model‑training/evaluation workflows
Ability to troubleshoot complex software, data, or model‑related issues
Required Credentials
Ability to otain a DoD Information Assurance Technician (IAT) Level II certification or higher (e.g., Security\+ CE, CCNA Security, CySA\+) within 3 months of hire if not currently held.
Must be a U.S. Citizen
Must hold a current or active DoD Secret clearance
Preferred Requirements
Degree in Computer Science, Data Science, ML/AI, Engineering, or related technical field
IAT Level II certification or higher (e.g., Security\+ CE, CCNA Security, CySA\+)
Experience with high‑fidelity training systems, simulation environments, or Navy combat systems
Experience deploying ML models in operational or real‑time systems (e.g., REST APIs, message queues, embedded inference)
Familiarity with ActiveMQ, messaging systems, or streaming‑data frameworks
Experience with MLOps tools such as GitLab CI/CD, Docker, Podman, Kubernetes, or virtualization technologies
Background in data analysis for mission systems, sensor data, or tactical environments
Experience with Jira, Git, or Subversion
Physical Qualifications
May require working in an office, industrial, shipboard, or laboratory environment. Must be capable of climbing ladders and tolerating confined spaces and a range of temperature conditions during shipboard or testing activities.
The listed salary range for this role is intended as a good faith estimate based on the role's location, expectations, and responsibilities. When extending an offer, HII's Mission Technologies division takes a variety of factors into consideration which include, but are not limited to, the role's function and a candidate's education or training, work experience, and key skills.
Meet HII’s Mission Technologies Division
Our team of more than 7,000 professionals worldwide delivers all\-domain expertise and advanced technologies in service of mission partners across the globe. Mission Technologies is leading the next evolution of national defense – the data evolution \- by accelerating a breadth of national security solutions for government and commercial customers. Our capabilities range from C5ISR, AI and Big Data, cyber operations and synthetic training environments to fleet sustainment, environmental remediation and the largest family of unmanned underwater vehicles in every class. Find the role that’s right for you. Apply today. We look forward to meeting you.
To learn more about Mission Technologies, click here for a short video: https://vimeo.com/732533072
HII is more than a job \- it’s an opportunity to build a new future. We offer competitive benefits such as best\-in\-class medical, dental and vision plan choices; wellness resources; employee assistance programs; Savings Plan Options (401(k)); financial planning tools, life insurance; employee discounts; paid holidays and paid time off; tuition reimbursement; as well as early childhood and post\-secondary education scholarships. Bonus/other non\-recurrent compensation is occasionally offered for qualified positions, and if applicable to this role will be addressed by the recruiter at the screening phase of application.
Why HII
We build the world’s most powerful, survivable naval ships and defense technology solutions that safeguard our seas, sky, land, space and cyber. Our workforce includes skilled tradespeople; artificial intelligence, machine learning (AI/ML) experts; engineers; technologists; scientists; logistics experts; and business administration professionals.
Recognized as one of America’s top large company employers, we are a values and ethics driven organization that puts people’s safety and well\-being first. Regardless of your role or where you serve, at HII, you’ll find a supportive and welcoming environment, competitive benefits, and valuable educational and training programs for continual career growth at every stage of your career.
Together we are working to ensure a future where everyone can be free and thrive.
All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, physical or mental disability, age, or veteran status or any other basis protected by federal, state, or local law.
Do You Need Assistance?
If you need a reasonable accommodation for any part of the employment process, please send an e\-mail to buildyourcareer@hii\-co.com and let us know the nature of your request and your contact information. Reasonable accommodations are considered on a case\-by\-case basis. Please note that only those inquiries concerning a request for reasonable accommodation will be responded to from this email address. Additionally, you may also call 1\-844\-849\-8463 for assistance. Press \#3 for HII Mission Technologies.
Salary Context
This $95K-$122K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $175K across 2162 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At HII, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $214,900 based on 6,420 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($108K) sits 50% below the category median. Disclosed range: $95K to $122K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
HII AI Hiring
HII has 2 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Arlington, VA, US, Virginia Beach, VA, US. Compensation range: $122K - $200K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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