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About This Role
Date: Jul 28, 2026
Location: Arlington, VA, Remote, United States
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Company: HII's Mission Technologies division
Requisition Number: 29442
Required Travel: 0 \- 10%
Employment Type: Full Time/Salaried/Exempt
Anticipated Salary Range: $180,000\.00 \- $200,000\.00
Security Clearance: Secret
Level of Experience: Senior
This opportunity resides with Warfare Systems (WS), a business group within HII’s Mission Technologies division. Warfare Systems comprises cyber and mission IT; electronic warfare; and C5ISR systems.
HII works within our nation’s intelligence and cyber operations communities to defend our interests in cyberspace and anticipate emerging threats. Our capabilities in cybersecurity, network architecture, reverse engineering, software and hardware development uniquely enable us to support sensitive missions for the U.S. military and federal agency partners.
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
Job Description
Join the growing Warfare Systems Business Group at HII\-Mission Technologies! We are seeking a Senior AWS Data Scientist 4 (AI/ML Engineer) to support the Defense Security Cooperation Agency (DSCA) Case Development Modernization (CDM) effort. In this high\-impact role, you will design, develop, and operationalize advanced AI/ML solutions on AWS GovCloud to modernize the Foreign Military Sales (FMS) case lifecycle, including the Defense Security Assistance Management System (DSAMS) Case Development and Training Modules. You will leverage machine learning, generative AI, and Retrieval\-Augmented Generation (RAG) techniques to enhance data transparency, accelerate case development timelines, enable intelligent automation, and support Executive Order 14268 goals for speed and accountability in security cooperation.
Essential Job Responsibilities
Designs, develops, and implements statistical and analytical methods, examines processes and systems to consolidate and analyze diverse data sets including structured, semi\-structured and unstructured.
Develops and sources software programs, algorithms, dashboards, information tools, and queries to clean, model, integrate and evaluate datasets.
Employs statistical concepts, linguistics and programming skills to develop related techniques and methods for analysis.
Keeps abreast of new analytic methodologies and technologies.
Collaborates with functional business units to drive solutions and directions and interprets and presents findings to enable business decisions
Design, develop, and operationalize AI\-enabled data solutions that ingest, transform, and analyze structured and unstructured data to support production machine learning, generative AI, and decision\-support capabilities.
Design, develop, and deploy production\-grade AI/ML models to support Case Development Modernization, including semantic search, intelligent document processing, predictive analytics for case timelines, and workflow automation.
Implement Retrieval\-Augmented Generation (RAG) architectures and generative AI solutions to improve data discovery, case line recommendations, and stakeholder decision support.
Develop and maintain modern data architectures that enable real\-time bi\-directional synchronization between legacy Oracle databases and new cloud\-native systems while ensuring data integrity and auditability.
Build scalable data pipelines, feature stores, and MLOps processes in IL5 DISA GovCloud environments using tools such as Databricks, SageMaker, or equivalent.
Collaborate with cross\-functional teams (Software Engineers, Data Engineers, Product Owners, and SMEs) in a SAFe Agile environment to translate FMS business requirements into AI/ML capabilities.
Ensure all AI/ML solutions comply with DoD standards including Zero Trust, RMF, Section 508, and applicable security controls while supporting automated ATO processes through SBOM generation and continuous monitoring.
Evaluate emerging AI technologies and recommend innovative applications to reduce technical debt and improve efficiency across the case lifecycle.
Develop analytic datasets and support visualizations that provide actionable insights to DSCA leadership and stakeholder.
Performs additional duties as assigned or required to advance mission goals
Minimum Qualifications
Experience developing and deploying production AI/ML solutions using modern frameworks.
Proficiency in Python and experience building production AI/ML systems.
Experience deploying, monitoring, and maintaining AI/ML workloads using could\-native ML platforms and MLOps practices.
Experience preparing, integrating, and managing structured and unstructured data that supports production AI/ML workloads.
Ability to work independently while thriving in collaborative team settings.
Self\-motivated initiator with strong problem\-solving skills and a proactive approach.
Clearance: Must possess and maintain an active Secret clearance at the time of consideration
Remote\-eligible position; must align with Eastern Time Zone core business hours
AI/ML Engineer IV
9 years relevant experience with Bachelors in related field; 7 years relevant experience with Masters in related field; 4 years relevant experience with PhD in related field; or High School Diploma or equivalent and 13 years relevant experience.
AI/ML Engineer V
15 years relevant experience with Bachelors in related field; 13 years relevant experience with Masters in related field; 10 years relevant experience with PhD or Juris Doctorate in related field; or High School Diploma or equivalent and 19 years relevant experience.
\*\*\*Salary level based on background, direct experience and education
Preferred Requirements
Advanced degree (MS or PhD) in Data Science, Computer Science, Statistics, or related field.
Experience implementing RAG architectures and AI\-driven semantic search capabilities.
Familiarity with Foreign Military Sales (FMS), DSAMS, or Security Cooperation processes.
Experience with Oracle databases, data migration, and hybrid legacy\-to\-modern architectures.
Knowledge of DoD IL5 environments, Zero Trust, and RMF processes.
Experience in SAFe Agile environments, including PI planning and Scrum/Kanban ceremonies.
Familiarity with React\-based frontends, Kotlin/Quarkus backends, and IBM Cognos Analytics.
Relevant certifications such as AWS Certified Machine Learning – Specialty or equivalent.
Physical Requirements
Ability to remain in a stationary position for prolonged periods while working at a computer.
Ability to operate a keyboard, mouse, and standard office equipment to perform analytical tasks.
Must be able to effectively communicate in virtual meetings, briefings, and secure collaboration environments.
Ability to review, analyze, and interpret digital data for extended periods with attention to detail and accuracy.
Occasional light lifting of documents or equipment up to 10 lbs, if needed for home\-office setup.
Must maintain a home work environment that meets company and government security requirements (e.g., controlled space for handling sensitive or FOUO information, if applicable).
Must be able to work assigned East Coast core business hours to support program and customer requirements.
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 $180K-$200K range is above the median 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. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($190K) sits 12% below the category median. Disclosed range: $180K to $200K.
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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