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Machine Learning Engineer Jobs in Huntsville, AL

IGNITE

MACHINE LEARNING ENGINEER

Huntsville, AL · On-site

Job Title MACHINE LEARNING ENGINEER Location Huntsville, AL US (Primary) Category Engineering Job Type Full-Time Career Level Experienced (Non-Manager) Education Bachelor's Degree Security Clearance ...

Bespoke Labs

Machine Learning Engineer

Huntsville, AL · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Varsity Tutors

Machine Learning Tutor

Huntsville, AL · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Decisive Intelligence Inc

AI Engineer

Huntsville, AL · On-site

Machine Learning Engineer Schedule: Full-time Shift: Day Job Travel: Yes, 10 % of the Time Minimum Clearance Required: Interim Secret Clearance Level Must Be Able to Obtain: Secret Potential for ...

Decisive Intelligence Inc

AI Engineer

Huntsville, AL · On-site

Machine Learning Engineer Schedule:Full-time Shift:Day Job Travel:Yes, 10 % of the Time Minimum Clearance Required:Interim Secret Clearance Level Must Be Able to Obtain:Secret Potential for Remote ...

Decisive Intelligence Inc

AI Engineer

Huntsville, AL

Machine Learning Engineer Schedule:Full-time Shift:Day Job Travel:Yes, 10 % of the Time Minimum Clearance Required:Interim Secret Clearance Level Must Be Able to Obtain:Secret Potential for Remote ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Huntsville, AL

Machine Learning Engineer information

See Huntsville, AL salary details

$31.2K

$127.7K

$191.9K

How much do machine learning engineer jobs pay per year?

As of Jul 27, 2026, the average yearly pay for machine learning engineer in Huntsville, AL is $127,672.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,600.00 and $153,700.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Huntsville, AL? The most popular types of Machine Learning Engineer jobs in Huntsville, AL are:
What are popular job titles related to Machine Learning Engineer jobs in Huntsville, AL? For Machine Learning Engineer jobs in Huntsville, AL, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Huntsville, AL look for? The top searched job categories for Machine Learning Engineer jobs in Huntsville, AL are:
What cities near Huntsville, AL are hiring for Machine Learning Engineer jobs? Cities near Huntsville, AL with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Huntsville, AL as of July 2026, with employment types broken down into 89% Full Time, 8% Part Time, and 3% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $127,672 per year, or $61.4 per hour.
MACHINE LEARNING ENGINEER

MACHINE LEARNING ENGINEER

Ignite Fueling Innovation

Huntsville, AL

Full-time

Posted 27 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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