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Machine Learning Defense Jobs (NOW HIRING)

Accelint

Machine Learning Engineer

Lyntris is a defense technology company that connects sensing to action across the connected ... We are seeking an experienced Machine Learning Engineer / NLP Engineer to develop intelligent ...

Spear AI

Machine Learning Engineer

Spear AI is a growing defense contracting company dedicated to delivering cutting-edge solutions that support our nation's security. They are seeking a skilled Machine Learning Engineer to build and ...

Hadrian

Machine Learning Engineer

Los Angeles, CA · On-site

Hadrian is a company focused on building autonomous factories for the aerospace and defense industries. As a Senior Machine Learning Engineer, you will design, build, and scale advanced software ...

CoVar

Machine Learning Engineer

Durham, NC · On-site

... Defense project experience • Active US security clearance (secret or higher) Company : CoVar is a leader in machine learning and artificial intelligence solutions. Founded in 2011, the company is ...

Society of Defense Financial Management

$125 - $150/hr

Machine Learning Engineer Accepting candidates LOCAL or wanting to relocate to Beavercreek, OH only ... Etegent Technologies is a defense-focused technology company with offices in Beavercreek and Blue ...

New

CoVar

Machine Learning Engineer

Durham, NC · On-site

... Defense project experience • Active US security clearance (secret or higher) Company : CoVar is a leader in machine learning and artificial intelligence solutions. Founded in 2011, the company is ...

1872 Consulting

Machine Learning Engineer

Austin, TX · On-site

Striveworks is a leader in Machine Learning Operations for highly regulated industries such as the Department of Defense/U.S. Military. They are seeking a Machine Learning Engineer to be a core ...

Spear AI

Machine Learning Engineer

Spear AI is a growing defense contracting company dedicated to delivering cutting-edge solutions that support our nation's security. They are seeking a skilled Machine Learning Engineer to build and ...

CoVar

Machine Learning Engineer

Durham, NC · On-site

Machine Learning Engineer About CoVar CoVar is a small AI/ML R&D software company in Durham, NC ... Department of Defense project experience * Active US security clearance (secret or higher) Benefits

ManTech International

Machine Learning Engineer

$128K - $214K/yr

... Defense, and Federal Civilian sectors. Dive into innovation in Digital Transformation ... The Machine Learning Engineer will leverage their strong technical background and knowledge to ...

Hadrian Automation

Machine Learning Engineer

Torrance, CA · On-site

$160K - $300K/yr

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling ... Previously worked in aerospace, defense, or manufacturing, and have experience working 3D/CAD/CAM ...

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Machine Learning Defense information

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$25.5K

$42.6K

$88K

How much do machine learning defense jobs pay per year?

As of Sep 9, 2026, the average yearly pay for machine learning defense in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What is machine learning defense?

Machine learning defense refers to techniques and strategies designed to protect machine learning models from various security threats, such as adversarial attacks, data poisoning, and model theft. These defenses can include methods like adversarial training, input sanitization, and robust model architectures. The goal is to ensure that machine learning systems remain accurate, reliable, and safe even when faced with malicious attempts to manipulate or exploit them. As machine learning becomes more widely adopted, the importance of effective defenses continues to grow.

What are some common challenges faced by professionals in machine learning defense roles, and how can they be addressed?

Professionals in Machine Learning Defense often encounter challenges such as staying ahead of adversarial attacks, managing model robustness, and keeping up with rapidly evolving threat landscapes. Addressing these challenges typically requires continuous learning, collaboration with cybersecurity and data science teams, and implementing rigorous testing and monitoring frameworks for deployed models. Proactively participating in industry forums and staying updated on the latest research also help in identifying emerging threats and mitigation strategies.

What are the key skills and qualifications needed to thrive as a machine learning defense professional, and why are they important?

To thrive as a Machine Learning Defense professional, you need a strong background in computer science, cybersecurity, and machine learning, often supported by degrees in these fields or related certifications. Familiarity with frameworks like TensorFlow or PyTorch, experience with adversarial machine learning techniques, and knowledge of security protocols are typically required. Critical thinking, problem-solving, and strong communication skills are essential for anticipating threats and collaborating with interdisciplinary teams. These skills ensure that AI systems remain robust and secure against evolving cyber threats, protecting sensitive data and organizational integrity.
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What states have the most Machine Learning Defense jobs?

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Machine Learning Defense jobs near you
Infographic showing various Machine Learning Defense job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 23% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Machine Learning Engineer

Remote

Accelint
See more jobs at Accelintexternal

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 3 days ago

Job description

Lyntris is a defense technology company that connects sensing to action across the connected battlespace. Lyntris brings together the talents of Accelint and Vitesse teams under one mission, with each contributing deep expertise within their domain. Combining differentiated hardware, software and mission expertise, Lyntris helps customers sense threats, make sense of complex conditions and act with greater speed, precision and confidence in contested environments.
Lyntris supports U.S. and allied defense organizations across every branch - including Navy, Army, Air Force, Space Force and allied partners - spanning strategic, operational and tactical missions and every domain: Space, Air, Land, Sea and Cyber. With more than 200 active defense programs, Lyntris works at every level of the mission, from national command authority to the tactical edge.
Solutions are designed by operators who understand the mission, engineered for the conditions that degrade or defeat standard systems, and built on an open, modular architecture that integrates into existing programs without requiring them to start over. Lyntris moves faster than the traditional defense cycle - with integrated design, build and test capabilities in-house - and delivers systems that sustain and endure long after initial fielding.
We are seeking an experienced Machine Learning Engineer / NLP Engineer to develop intelligent document understanding solutions powered by modern natural language processing (NLP) and large language models (LLMs). In this role, you will build and optimize pipelines that transform complex technical documentation into structured, machine-actionable knowledge. You will work with transformer models, retrieval-augmented generation (RAG), and advanced document processing techniques to enable search, question answering, summarization, and information extraction across engineering and technical content.
Duties & Responsibilities
  • Design, develop, and maintain NLP pipelines for technical and structured document understanding, including information extraction, summarization, semantic search, and question answering.
  • Build and optimize LLM-powered applications using transformer-based models, including fine-tuning, prompt engineering, and retrieval-augmented generation (RAG) architectures.
  • Process and analyze complex technical corpora, including engineering manuals, specifications, technical reports, drawings, tables, and figures.
  • Develop methods to convert unstructured and semi-structured documents into structured, machine-actionable knowledge for downstream applications.
  • Implement scalable machine learning solutions using Python and modern ML frameworks such as PyTorch and Hugging Face.
  • Evaluate model performance, improve accuracy, and optimize inference pipelines for production environments.
  • Collaborate with cross-functional teams, including software engineers, data scientists, and subject matter experts, to define requirements and deliver AI-enabled document intelligence solutions.
  • Performs other duties as assigned.

Required Qualifications
  • Bachelor's degree in Computer Science, Data Science, AI/Machine Learning, or a related technical field (or equivalent practical experience).
  • 2-4 years of experience building NLP pipelines for technical or structured document understanding, including extraction, summarization, semantic search, and question answering.
  • Hands-on experience with large language models (LLMs) and transformer architectures (BERT and successor models), including fine-tuning, prompt engineering, pipeline orchestration, and retrieval-augmented generation (RAG).
  • Experience processing complex technical documentation such as engineering manuals, specifications, technical artifacts, tables, and figures.
  • Strong proficiency in Python and modern machine learning frameworks, including PyTorch and Hugging Face Transformers.
  • Demonstrated experience converting unstructured text into structured, machine-actionable knowledge.
  • Currently holds an active U.S. national security clearance or be able to receive and maintain one.

Preferred Qualifications (Not Required)
  • Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a related field.
  • Experience deploying and maintaining production-scale NLP or LLM applications.
  • Familiarity with vector databases, embedding models, and semantic retrieval systems.
  • Experience with document parsing, OCR, layout-aware models, or multimodal document understanding.
  • Experience working with engineering, manufacturing, aerospace, defense, or other highly technical datasets.
  • Knowledge of MLOps practices, model monitoring, CI/CD pipelines, and cloud-based AI infrastructure.
  • Active-duty military experience.

Physical Requirements
  • Prolonged periods sitting at a desk and working on a computer.
  • Must be able to lift up to 15 pounds at times.

Clearance Requirements
Some positions will require access to U.S. National Security information. Positions that require this access will be required to receive and maintain a U.S. government personnel security clearance (PCL). In order to qualify for this position, the candidate must be a US Citizen and either currently possess this National Security eligibility or be able to complete the investigation application process with a favorable determination and maintain that eligibility throughout their employment. To learn more about the security clearance process please access this link.
EEOC & Know Your Rights
Lyntris companies are Equal Opportunity Employers. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, status as a protected veteran or any other status protected by applicable federal, state, and local law. We ensure that all employment decisions, including hiring, promotion, compensation, and other terms and conditions of employment, are based on merit, qualifications, and business needs. For more information about your rights, please review the "Know Your Rights" poster from the Equal Employment Opportunity Commission (EEOC). Know your Rights: English Spanish
Pay Scales & Benefits
The listed pay scale reflects the broad, minimum to maximum, pay scale for this position for the location for which it has been posted and is not a guarantee of compensation or salary. Other compensation considerations may include, but are not limited to, job responsibilities, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, or other applicable factors.
Benefits include...
• Paid Time Off
• Paid Company Holidays
• Medical, Dental & Vision Insurance
• Optional HSA and FSA
• Base and Voluntary Life Insurance
• Short Term & Long-Term Disability Insurance
• 401k Matching
• Employee Assistance Program

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