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Machine Learning Defense Jobs in Colorado (NOW HIRING)

Agile Defense

Data Scientist

Colorado Springs, CO

... Defense's CDAO ADA IR program. This role is part of a multidisciplinary team integrating advanced analytics, machine learning, and engineering practices into mission-critical environments at ...

Deloitte

Cyber - SecOps - Consultant

Denver, CO · On-site

... machine learning for cyber defense and operations. The team serves as a trusted advisor and managed service provider, bringing capability and capacity across security data modernization, DataOps, AI ...

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Machine Learning Defense information

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.

What are popular job titles related to Machine Learning Defense jobs in Colorado?

For Machine Learning Defense jobs in Colorado, the most frequently searched job titles are:

What job categories do people searching Machine Learning Defense jobs in Colorado look for?

The top searched job categories for Machine Learning Defense jobs in Colorado are:

What cities in Colorado are hiring for Machine Learning Defense jobs?

Cities in Colorado with the most Machine Learning Defense job openings:

Machine Learning Defense jobs near you
Infographic showing various Machine Learning Defense job openings in Colorado as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 22% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Machine Learning Engineer

nou Systems, Inc.

Colorado Springs, CO • On-site

Full-time

Re-posted 3 days ago

Job description

Job Summary:
nou Systems, Inc. is a 100% ESOP company focused on solving challenging defense problems. They are seeking a Machine Learning Engineer to design, develop, and deploy machine learning capabilities for defense applications, collaborating with teams to transition ML concepts into practical solutions.
Responsibilities:
• Develop, train, evaluate, and analyze machine learning models using Python and PyTorch, writing modular, maintainable, and testable code.
• Build backend software components that support ML workflows, data processing, model evaluation, and system integration.
• Help identify, prepare, and validate training and evaluation datasets.
• Implement and adapt ML methods from open literature, including supervised learning and deep learning approaches.
• Work in Linux-based, containerized development environments using VS Code Dev Containers, Remote-SSH, Docker/Podman, and contribute to continuous improvement of development processes.
• Use GitLab-based workflows for source control, issue tracking, merge requests, code review, and collaboration.
• Communicate technical results clearly through written documentation, presentations, and team discussions.
• Support multiple project teams and help translate ML concepts into practical engineering solutions.
Qualifications:
Required:
• Bachelor’s degree in computer science, mathematics, software engineering, data science, or a closely related technical field.
• 3+ years of professional experience in machine learning, data science, or backend software development.
• Hands-on experience developing, training, or evaluating deep learning models using PyTorch.
• Professional experience building backend software, data pipelines, APIs, or system integration components.
• U.S. citizenship and the ability to obtain a Secret security clearance.
Preferred:
• Strong communication skills, intellectual curiosity, and comfort working across ML, software, and mission-domain teams. Our work often requires creative, multidisciplinary approaches.
• Understanding of core ML and statistical concepts (bias-variance tradeoff, data mismatch, sample sufficiency)
• Comfort with self-direction. You'll work with our top technical talent, but we're looking for evidence you can diagnose a problem and approach it strategically.
• Experience with Docker, Podman, or similar containerization tools, including editing Dockerfiles or container configuration.
• Experience with ML tools (MLflow, Optuna, or PyTorch Lightning)
• Experience with RL development using Gymnasium and Ray RLlib.
• Experience with LLMs, generative AI tools, vector databases, or frameworks such as LangChain or LlamaIndex.
• Familiarity with CI/CD pipelines, Kubernetes, DevSecOps practices, secure artifact repositories, or deployment in restricted DoD environments.
Company:
no Systems is a consultant offering engineering and technical services to the government in Huntsville, Alabama. Founded in 2011, the company is headquartered in Huntsville, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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