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Machine Learning Defense Jobs in Alabama (NOW HIRING)

IGNITE

MACHINE LEARNING ENGINEER

Huntsville, AL · On-site

Job Title MACHINE LEARNING ENGINEER Location Huntsville, AL US (Primary) Category Engineering Job ... defense intelligence, EMSO, advanced analytics, and programmatic domains. As an employee-owned ...

Tocaro Blue

Senior Machine Learning Researcher

Birmingham, AL · On-site

$132K - $160K/yr

... experienced machine learning researcher ready to push the limits of AI in one of the toughest ... Your work will fuel products used by: • Defense customers developing USVs/ASVs for the U.S. Navy ...

Starfish

AI/ML Engineer

Redstone Arsenal, AL · On-site

... Machine Learning (AI/ML) Engineer to join our AI/ML team. The candidate will support the Missile Defense Agency's (MDA) Ground Test scenario design team. Our team is comprised of scenario design ...

Nou Systems Inc

DevOps Engineer

Huntsville, AL · On-site

$120K - $165K/yr

... defense, battle management, and related domains. You will help deploy, scale, and standardize machine learning development workflows in support of Small Business Innovation Research (SBIR) and Small ...

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Machine Learning Defense information

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers, AI research directors, or chief AI officers, often requiring advanced skills in deep learning, data science, and software engineering. These positions usually involve leadership responsibilities, extensive experience, and may include stock options or bonuses as part of compensation packages.

How much does Lockheed Martin pay AI?

As a Machine Learning Defense professional at Lockheed Martin, salaries typically range from $80,000 to over $130,000 annually, depending on experience, education, and specific role. Compensation may also include benefits such as health insurance, retirement plans, and performance bonuses, with opportunities for career advancement in defense and aerospace sectors.

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 jobs pay $2000 a day?

In the field of Machine Learning Defense, highly specialized roles such as senior machine learning engineers, AI security consultants, or cybersecurity analysts working on AI systems can command daily rates of around $2000 or more, especially with extensive experience, advanced certifications, and working on critical projects. These positions often require expertise in AI algorithms, cybersecurity, and relevant tools like Python, TensorFlow, or cybersecurity frameworks, and may involve consulting or contract work with flexible schedules.

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.

Which 3 jobs will survive AI?

In the field of Machine Learning Defense, roles such as cybersecurity analysts, AI security specialists, and data scientists are likely to persist as they require complex judgment, domain expertise, and ongoing adaptation to evolving threats. These jobs involve critical thinking, understanding of adversarial AI techniques, and specialized skills that are difficult to fully automate. Continuous learning and certifications in cybersecurity or AI are valuable for staying relevant in these roles.

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 popular job titles related to Machine Learning Defense jobs in Alabama? For Machine Learning Defense jobs in Alabama, the most frequently searched job titles are:
What job categories do people searching Machine Learning Defense jobs in Alabama look for? The top searched job categories for Machine Learning Defense jobs in Alabama are:
What cities in Alabama are hiring for Machine Learning Defense jobs? Cities in Alabama with the most Machine Learning Defense job openings:
Machine Learning Defense jobs near you
MACHINE LEARNING ENGINEER

MACHINE LEARNING ENGINEER

Ignite Fueling Innovation

Huntsville, AL

Full-time

Posted 24 days ago

Job description

Igniters operate in the world's most demanding environment. Igniters are self-motivated, mission-driven, and relentless in solving the Warfighters' hardest problems. We move fast, think differently, and execute with precision to tackle high-stakes challenges across AI/ML, space and missile defense intelligence, EMSO, advanced analytics, and programmatic domains.

As an employee-owned SDVOSB headquartered in Huntsville, AL, our team delivers mission-critical impact for the Army, Air Force, Space Force, MDA, NASA, DIA, and FBI. Ignite exists to outpace the threat and deliver results that matter in the moments that count. Ignite is currently seeking a driven, detail-oriented Machine Learning Engineer to join our team supporting the Missiles and Space Intelligence Center in Huntsville, AL.

This position is expected to be on-site. The team will work with technologies including: Open source, commercial, and government software packages such as Docker, Python, Jupyter Notebooks, PostgreSQL, and other tools. Leverage GitOps patterns and CI/CD with tools like GitLab and GitHub.Responsibilities include, but are not limited to: Integrate ML systems with other software components, ensuring that machine learning pipelines work within the overall product architecture

Manage the transition from prototype to production, including setting up model deployment pipelines and monitoring solutions. Construct optimized data pipelines to feed ML models; run tests and experiments and document findings. Monitor model performance post-deployment including managing model drift, rollback, and failure scenarios.

Write clean, testable, maintainable code in Python and other languages. Job Requirements and Qualifications: A minimum of 12 years of work experience, with 1-3 years of experience working with ML frameworks TS/SCI with ability to obtain CI Polygraph after onboarding. Degree in Computer Science, Statistics, Mathematics, Physics or another quantitative field.

1-3 years of experience working with ML frameworks. Programming proficiency in Python and extensive knowledge of ML frameworks, libraries data structures, and data modeling. Solid understanding of the full ML development lifecycle.

Experience working with SQL and NoSQL databases. Experience with both Linux and Windows operating systems. Knowledge of CI/CD and Agile methodologies.

Understanding of software design and system integration. Preferred Qualifications: Experience with petabyte scale data sets Experience with multi-INT analytics Experience deploying, monitoring, and scaling models in production environments Education Requirements: Master's degree in a related field with 12 years of experience or a bachelor's degree in a related field with 17 years of experience. Other Requirements: Must be a US citizen and be able to obtain and hold an active TS/SCI Clearance with CI Polygraph.Responsibilities include, but are not limited to: Integrate ML systems with other software components, ensuring that machine learning pipelines work within the overall product architecture

Manage the transition from prototype to production, including setting up model deployment pipelines and monitoring solutions. Construct optimized data pipelines to feed ML models; run tests and experiments and document findings. Monitor model performance post-deployment including managing model drift, rollback, and failure scenarios.

Write clean, testable, maintainable code in Python and other languages. Job Requirements and Qualifications: A minimum of 12 years of work experience, with 1-3 years of experience working with ML frameworks TS/SCI with ability to obtain CI Polygraph after onboarding. Degree in Computer Science, Statistics, Mathematics, Physics or another quantitative field.

1-3 years of experience working with ML frameworks. Programming proficiency in Python and extensive knowledge of ML frameworks, libraries data structures, and data modeling. Solid understanding of the full ML development lifecycle.

Experience working with SQL and NoSQL databases. Experience with both Linux and Windows operating systems. Knowledge of CI/CD and Agile methodologies.

Understanding of software design and system integration. Preferred Qualifications: Experience with petabyte scale data sets Experience with multi-INT analytics Experience deploying, monitoring, and scaling models in production environments Education Requirements: Master's degree in a related field with 12 years of experience or a bachelor's degree in a related field with 17 years of experience. Other Requirements: Must be a US citizen and be able to obtain and hold an active TS/SCI Clearance with CI Polygraph.

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