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About This Role
Clearance Required:
Ability to Obtain a Top Secret
Education Required:
BA/BS
US Citizenship:
Required
Summary
The MIL Corporation is seeking a highly motivated AI and Automation Engineer (Business Analysis, Senior Analyst) to help implement intelligent automation solutions for a federal agency. The ideal candidate will focus on business innovations, continuous improvement projects, and the implementation of process automation and data tools leveraging Microsoft Azure, AI, Microsoft Power Platform, and Palantir Foundry. This role involves providing visionary leadership for the AI development and Innovation team, driving initiatives that increase effectiveness, productivity, and customer satisfaction while acting as a liaison between systems development, computer operations, and accounting groups.
This position is eligible for a remote schedule. The schedule is subject to change based on company/contract requirements.
Responsibilities
- Design and develop AI Applications using machine learning (ML), Intelligent Character Recognition (ICR), and Large Language Models (LLM).
- Design, develop, set up, test, and monitor Robotic Process Automation (RPA) bots using Microsoft Power Platform, focusing on scalability, extensibility, and optimum efficiency without risk of error.
- Optimize and troubleshoot intelligent automations (AI\+RPA) to enhance performance and functionality.
- Manage the Microsoft Azure AI Foundry and related Azure resources needed for AI driven use cases.
- Conduct requirements gathering and analysis via user groups, interviews, and regulatory research.
Travel
None
Required Qualifications
- Minimum of 5 years of information technology professional experience as an analyst, programmer, or business/process.
- Experience working as a member of a team performing life cycle design/development/implementation operations or functional analysis.
- Ability to work independently, autonomously, and take initiative without being directed, while also working well within a team.
- Great analytical and debugging skills with a "big picture" approach and the ability to delve into details.
- Strong oral and written communication skills.
- Ability to direct project participants, brief all levels of management on project status, and build strong professional networks.
Desired Qualifications
- Experience with Microsoft Azure Cloud environments, and AI Applications.
- Expertise in designing, developing, and deploying Microsoft Power Platform solutions
- Experience in process mapping, requirements gathering, performing root cause analysis, auditing financial transactions/software, facilitating training, and project management.
- Understanding of the software development lifecycle, operational impact analysis, preparing test plans, and performing User Acceptance Testing (UAT).
- Exceptional ability to synthesize complex information, balance competing priorities, and maintain adaptability in a dynamic environment.
Education
Required \- High School Diploma
Desired \- BA/BS degree in Information Technology (or related field)
Clearance
Must be eligible to obtain a Secret clearance and be able to upgrade to a Top Secret (TS) clearance as required
Compensation
The MIL Corporation values your contributions and offers a range of benefits to support your overall well\-being. We are pleased to offer a comprehensive range of benefits to our full\-time employees which include health, life, disability, and retirement plans, as well as paid time off, opportunities for professional growth and tuition assistance. Additional benefits and incentives may also apply, which will be communicated during the hiring process.
For this position, the projected compensation range is $100,000 \- $130,000 per year. This estimate represents the typical salary range and is just one part of MIL’s complete compensation package. Final salary for this position is determined based on factors such as individual qualifications, education, experience, and contractual limitations. Learn more on the MIL Careers page.
Why MIL?
The MIL Corporation (MIL) is a dynamic workforce of industry professionals who deliver world\-class solutions in cyber, engineering, financial management, and information technology – and we are looking for candidates like you! MIL offers opportunities for professionals at all stages of their careers, from early\-career candidates to experienced industry professionals. We are known for a collaborative, people\-first culture where employees are supported, valued, and encouraged to grow. This commitment to our people and our work is reflected in the industry and workplace awards MIL has received over the years.
- 2021 \- 2024, Top Workplaces USA award (Energage)
- 2017 \- 2025 Top Workplaces Award, Greater Washington Area (The Washington Post)
- 2018 \- 2025 Certified Great Workplace, Great Place to Work®
+ 2021 \- 2025, Best Workplaces in Consulting \& Professional Services™
+ 2021 Fortune Best Workplaces for Millennials™
+ 2018 Fortune, Great Place to Work: Best Place to Work for Diversity
- 2017, 2020 \- 2025 Top Workplace Award, South Carolina (Greenville Business Magazine, Columbia Business Monthly, and Charleston Business Magazine)
- 2025 Corporate Partnership Award, Association of Fundraising Professionals, Maryland Chapter
- 2025 Moxie Award, GovCon Category
- 2024 Patriot Award, Employer Support of the Guard and Reserve (ESGR), Department of Defense
- 2022 Freedom Award, Employer Support of the Guard and Reserve (ESGR), Department of Defense
- 2018, Above \& Beyond Award, Employer Support of the Guard and Reserve (ESGR), Department of Defense
If your goal is to help the federal government deploy leading technologies, improve financial management, or defend the nation in cyberspace, MIL welcomes you. Become a part of something greater, where you, the people, make the difference.
Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by state or federal law.
Salary Context
This $100K-$130K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $180K across 1841 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 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At The MIL Corporation, 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 $218,750 based on 3,817 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($115K) sits 47% below the category median. Disclosed range: $100K to $130K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
The MIL Corporation AI Hiring
The MIL Corporation has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $130K - $130K.
Remote Work Context
Remote AI roles pay a median of $185,334 across 717 positions. About 14% of all AI roles offer remote work.
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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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