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About This Role
THOR Solutions is actively seeking a highly motivated Lead Software \& AI Engineer to support an upcoming contract at the Naval Information Warfare Center Pacific (NIWC PAC) in San Diego, CA. The position will design, develop, and integrate cutting\-edge Machine Learning (ML), Artificial Intelligence (AI), and Large Language Model (LLM) capabilities into Navy C2 decision support systems. This role is central to advancing automated decision aids that enhance warfighter situational awareness and accelerate the kill chain.
An ideal candidate will have significant hands\-on development experience using microservices, containers, and Kubernetes, as well as experience developing/integrating ML, AI, and LLM into operational systems.
This contract is expected to begin in or around December 2026\.
Typical Responsibilities:* Develop ML/AI/Operations Research (OR) methods to interpret Common Operational Picture (COP) displays and generate alerts based on CCIRs and predictive Enemy Courses of Action (ECOAs)
- Design and implement dynamic/probabilistic decision automation tools using ML/AI, Generative AI (GENAI), and LLMs
- Develop Natural Language Processing (NLP) methods for parsing and interpreting Navy\-wide and CSG OPTASKS and Pre\-Planned Responses (PPRs)
- Build, test, and refine Large Language Models tailored to operational Navy requirements
- Integrate GENAI capabilities into existing C2 software architectures
- Develop software products utilizing microservices, containers, service mesh, and Kubernetes
- Apply cybersecurity best practices throughout the software development lifecycle
Location: Full time onsite, split between the NIWC PAC facility and THOR’s local offices in San Diego, CA.
California Alternative Work Week Schedule: This position may utilize the California Alternative Work Week schedule: 9\-hours each day Monday – Thursday. Fridays will alternate as either 8\-hour days or non\-working days. In a two\-week period, this totals 80 working hours.
Anticipated Travel: Up to 10% travel is anticipated to primarily CONUS locations.
Typical Physical Activity: Desk/computer work in an office environment. May involve: repetitive motion.
Typical Pay Range: The anticipated pay for this position in the identified location(s) is $158,000/year. Actual compensation offered will be based upon individual factors including education, qualifications, and experience.
Existing TOP SECRET/SCI Security Clearance Required: This position requires a TOP SECRET/SCI security clearance. Candidates must either already possess an active or interim TS/SCI clearance OR be TS/SCI Eligible with a completed Tier 5 investigation. Only U.S. citizens are eligible for a security clearance; therefore, only current U.S. citizens will be considered for this position.
Required Knowledge, Skills, and Abilities:* At least five (5\) years hands\-on software development using microservices, containers, and Kubernetes.
- Experience developing/integrating Machine Learning/Artificial Intelligence (ML/AI) or Large Language Models (LLM) into operational systems.
- Possess one or more of the following active certifications, to meet DoD 8140/8570 IAT Level II and/or intermediate proficiency level baseline for CSWF approval:
+ CompTIA Security\+ (Sec\+)
+ Cisco Certified Network Associate\-Security (CCNA\-Security)
+ CompTIA Cybersecurity Analyst (CySA\+)
+ EC\-Council Certified Network Defender (CND)
+ CompTIA Advanced Security Practitioner (CASP\+)
+ Cisco Certified Network Professional (CCNP)
+ ISACA Certified Information Systems Auditor (CISA)
+ ISC2 Certified Information Systems Security Professional (CISSP) or Associate
- Proficient with common productivity software.
- Excellent communication skills.
Additional Preferred Knowledge, Skills, and Abilities:* Experience with Python, TensorFlow, PyTorch, or similar ML frameworks.
- Familiarity with Navy C2 systems, particularly MTC2 or C2X.
- Experience developing software for DoD DevSecOps pipelines (e.g., Overmatch Software Armory).
- Knowledge of Operations Research techniques and optimization algorithms.
Benefit Offerings: Along with competitive pay, THOR offers a comprehensive benefits package including:
- Paid Time Off (accrued)
- Paid Holidays
- 401(k) with employer match and traditional/Roth options
- Medical Insurance (3 plan options) \+ TRICARE Supplemental Coverage
- Dental Insurance (2 plan options)
- Vision Insurance Plan
- Healthcare and Dependent Care Flexible Spending Accounts
- Commuter/Transit Benefits
- Basic Life/AD\&D, Short\-Term and Long\-Term Disability Insurance
- Supplemental Life Insurance
- Pet Benefits
- Legal Resources
- ID Theft Benefits
- Employee Assistant Plan and Work\-Life Program
- Voluntary Leave Transfer Program
- Tuition Reimbursement Program
- Employee Referral Program
Please be aware that many of our positions require the ability to obtain a security clearance. Security clearances may only be granted to U.S. citizens.
Founded in 2009, THOR Solutions, LLC (THOR) is a rapidly growing Center for Veteran’s Excellence (CVE) verified Service\-Disabled Veteran\-Owned Small Business (SDVOSB) providing mission critical support across the Department of Defense, Department of Homeland Security, federal civilian agencies and commercial maritime industry, worldwide. THOR provides innovative and tailored expertise in multidisciplinary engineering, project and program management, business and financial management, technical support, integrated logistics support, training support, fleet support, corporate operations support, assessments and studies. THOR is privileged to deliver service solutions to the nation’s most complex military, public sector and industry challenges.
THOR is proud to be an Equal Opportunity Employer, including veterans and individuals with disabilities. THOR considers all qualified applicants for employment without regard to legally protected characteristics. This policy applies to all terms and conditions of employment.
If you are an individual with a disability and would like to request a reasonable accommodation as part the employment selection process, please contact us at [email protected] or (571\) 215\-0077\.
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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 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At Thor Solutions, LLC, 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 $181,170 based on 12,692 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Thor Solutions, LLC AI Hiring
Thor Solutions, LLC has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in San Diego, CA, US.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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