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AI / ML Engineer

Pay
Pay not listedSimilar roles state $166K–$240K
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting

What you’ll work on

Full posting
  • Design and maintain classical and deep learning models

  • Build LLM applications and RAG pipelines with vector databases

  • Develop AI assurance tools for robustness, bias, and adversarial testing

  • Optimize and deploy models for production and edge environments

  • Secure model and data pipelines against adversarial ML threats

From the employer’s posting
Design, develop, and maintain machine learning models, from classical algorithms (regression, tree ensembles, clustering) to modern deep learning architectures.
Build LLM-enabled applications and retrieval-augmented generation (RAG) pipelines, including vector embedding generation, vector database integration, and prompt/context engineering.
Develop AI assurance and evaluation tooling: robustness testing, bias/fairness analysis, model traceability, red-team/adversarial testing, and audit artifact generation.
Optimize and deploy models for production and edge environments (quantization, compression, containerized inference, ONNX/TensorRT).
Implement secure model and data pipelines, defend against adversarial ML threats, and ensure supply-chain integrity (SBOM) for AI components.

What you’ll bring

All qualifications

Core experience

  • Bachelor's degree or equivalent experience in CS/CPE/EE/Data Science (or related field).
  • Understanding of computer security principles and secure software development lifecycle (SSDLC) practices.
  • Proven experience in one or more: ML/LLM development, assurance/evaluation tooling, or deploying edge computing solutions.
  • Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Proficiency in Python and at least one additional language (Java, C++).
  • Strong understanding of data structures, data modeling, and software architecture.
Qualification wording
Bachelor's degree or equivalent experience in CS/CPE/EE/Data Science (or related field).
Understanding of computer security principles and secure software development lifecycle (SSDLC) practices.
Proven experience in one or more: ML/LLM development, assurance/evaluation tooling, or deploying edge computing solutions.
Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
Proficiency in Python and at least one additional language (Java, C++).
Strong understanding of data structures, data modeling, and software architecture.
Education & alternatives
Minimum Requirements: - Bachelor's degree or equivalent experience in CS/CPE/EE/Data Science (or related field). - Proven experience in one or more: ML/LLM development, assurance/evaluation tooling, or deploying edge computing solutions.

About DESE Research

For the past 44 years, DESE has provided industry-leading technical and engineering solutions in the fields of Defense, Energy, Space, and Environment.

In the employer’s words · Read in context

Apply at DESE Research

Posting record

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Open 3 monthsWe first saw this posting 95 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Aug 8, 202695 days ago
Recorded sightings
50
Last seen by us
Nov 12, 2026
Employer says posted
Aug 5, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$166K–$240K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 1,383 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 95

Up longer than most. Similar jobs usually come down between day 8 and day 75.

From 5,254 similar postings that came down. Coming down is not always a hire.

DESE Research is hiring

1 open job

  • No new data jobs since August
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • C++
  • Java
  • MATLAB
  • Python
  • AWS
  • Azure
  • GCP
  • PyTorch
  • scikit-learn
  • TensorFlow
Where the posting names them
- Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn. - Proficiency in Python and at least one additional language (Java, C++). - Strong understanding of data structures, data modeling, and software architecture.
- Platform & DevSecOps: REST APIs, CI/CD for software and ML systems, SAST/DAST, Infrastructure-as-Code, cloud platforms (AWS, Azure, GCP). - Domain: Familiarity with computer networking, secure system integration for mission platforms, and test/V&V support (Python/MATLAB analysis). - Contributions to open-source AI/ML projects; experience deploying AI models in production, classified, or embedded environments.
- Edge & Deployment: ONNX/TensorRT, quantization/compression, ARM/NVIDIA Jetson/DSP targets, containerized inference, MLOps in controlled/classified environments. - Platform & DevSecOps: REST APIs, CI/CD for software and ML systems, SAST/DAST, Infrastructure-as-Code, cloud platforms (AWS, Azure, GCP). - Domain: Familiarity with computer networking, secure system integration for mission platforms, and test/V&V support (Python/MATLAB analysis).
- Proven experience in one or more: ML/LLM development, assurance/evaluation tooling, or deploying edge computing solutions. - Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn. - Proficiency in Python and at least one additional language (Java, C++).

Your next step

Complete your application on deseresearch.applicantpro.com. The employer’s form will show what is required.

Already applied? Track this application

Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 13% over the last 6 weeks compared with the 6 before.

Weekly new ML Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 617, the most 1,122, and the latest week had 1,122.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

DESE's Cyber Works and Digital Engineering teams design, build, and integrate emerging AI/ML technologies to harden and secure the systems that defend the nation, across ground, missile defense, space, and installation infrastructure S&T programs. We're expanding our Secure AI practice to build and assure trusted, robust AI/ML solutions that interpret complex datasets, predict outcomes, and automate decision-making in support of critical military platforms.

This is a consolidated announcement covering multiple tracks; your assignment may emphasize one or a blend of: Classic ML & Predictive Modeling, LLM/GenAI Applications, AI Assurance & Responsible AI, Edge AI/ML Deployment, and hardening AI/ML systems against adversarial threats. All tracks require independent research, cross-functional collaboration, and the ability to clearly communicate complex technical work to stakeholders.


Core Responsibilities:

  • Design, develop, and maintain machine learning models, from classical algorithms (regression, tree ensembles, clustering) to modern deep learning architectures.
  • Build LLM-enabled applications and retrieval-augmented generation (RAG) pipelines, including vector embedding generation, vector database integration, and prompt/context engineering.
  • Develop AI assurance and evaluation tooling: robustness testing, bias/fairness analysis, model traceability, red-team/adversarial testing, and audit artifact generation.
  • Optimize and deploy models for production and edge environments (quantization, compression, containerized inference, ONNX/TensorRT).
  • Implement secure model and data pipelines, defend against adversarial ML threats, and ensure supply-chain integrity (SBOM) for AI components.
  • Conduct data processing/analysis to improve model accuracy; document and present development processes and assurance evidence to stakeholders.
  • Contribute to Agile, team-based planning and estimating in a fast-paced, collaborative environment.

Minimum Requirements: 

  • Bachelor's degree or equivalent experience in CS/CPE/EE/Data Science (or related field).
  • Proven experience in one or more: ML/LLM development, assurance/evaluation tooling, or deploying edge computing solutions.
  • Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Proficiency in Python and at least one additional language (Java, C++).
  • Strong understanding of data structures, data modeling, and software architecture.

Highlighted Skills & Experience: 

  • Modern AI: LLM frameworks and application development; vector embeddings and vector databases; RAG architectures; prompt/context engineering; LLM fine-tuning; model evaluation and benchmarking.
  • Classic ML: Feature engineering, model selection/tuning, statistical analysis, and predictive modeling across structured and unstructured data.
  • AI Assurance: Responsible AI practices (robustness, bias/fairness, traceability); adversarial ML defenses; red-team testing; auditability and compliance documentation.
  • Edge & Deployment: ONNX/TensorRT, quantization/compression, ARM/NVIDIA Jetson/DSP targets, containerized inference, MLOps in controlled/classified environments.
  • Platform & DevSecOps: REST APIs, CI/CD for software and ML systems, SAST/DAST, Infrastructure-as-Code, cloud platforms (AWS, Azure, GCP).
  • Domain: Familiarity with computer networking, secure system integration for mission platforms, and test/V&V support (Python/MATLAB analysis).
  • Contributions to open-source AI/ML projects; experience deploying AI models in production, classified, or embedded environments.
  • Understanding of computer security principles and secure software development lifecycle (SSDLC) practices.

Why This Role Matters:
You'll join a high-impact team solving some of the DoD's hardest problems in AI-enabled system security, building the next generation of trusted, auditable, and mission-ready AI for national defense.

About DESE

For the past 44 years, DESE has provided industry-leading technical and engineering solutions in the fields of Defense, Energy, Space, and Environment. As a small, family-oriented business, DESE provides a compelling benefits package including a generous profit-sharing plan, competitive salaries, and perhaps most importantly, the opportunity to work alongside talented professionals leveraging cutting-edge technologies to solve complex and engaging problems.

Why employees love working for DESE:

At DESE, we are committed to creating a company that is known for its respect and care for employees. We understand that happy employees are what keeps our business going and we strive to provide the best opportunities for each individual working on our team! Here are a few reasons you will love working here:

  • Competitive health, dental and vision insurance with affordable premiums
  • Flexible work schedules
  • Two different flexible spending account options
  • Company paid life insurance with options for employee paid additional
  • Performance bonus program
  • Education reimbursement program
  • Company paid personal leave for approved philanthropic activities
  • Vacation, Sick & Holiday leave
  • Robust 401k profit sharing plan
  • Opportunities for internal promotions
  • Employee referral incentive program
  • Rewards and gifts for service anniversaries

Disability Accommodation for Applicants - DESE Research, Inc. is an Equal Employment Opportunity employer and provides reasonable accommodation for qualified individuals with disabilities and disabled veterans in its job application procedures. If you have any difficulty using our online system and you need an accommodation due to a disability, you may use the following alternative email address or phone number to contact us about your interest in employment with us: hrandsecurity@dese.com or 256-837-8004x123.

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Huntsville, AL, 35805, US

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