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Contract Machine Learning Software Engineer Jobs in Alabama

Astrion

Machine Learning Engineer

Huntsville, AL · On-site

Overview Machine Learning Engineer JOB LOCATION: Huntsville, Al JOB STATUS: Full-time CLEARANCE: TS ... Open source, commercial, and government software packages such as Docker, Python, Jupiter Notebooks ...

Astrion

Machine Learning Engineer

Huntsville, AL · On-site

$135K - $150K/yr

Overview Machine Learning Engineer JOB LOCATION: Huntsville, Al JOB STATUS: Full-time CLEARANCE: TS ... Open source, commercial, and government software packages such as Docker, Python, Jupiter Notebooks ...

Quantum-Systems,-Inc

Software Engineer

Huntsville, AL · On-site

$125 - $150/hr

As a Software Engineer at Quantum-Systems you will play a critical role in solving challenges ... contract requirements. Preferred Qualifications: * 3+ years of machine learning development

IGNITE

SOFTWARE ENGINEER

Huntsville, AL · On-site

They are currently seeking a driven Software Engineer to support the Army Logistics Engineering ... Machine Learning (ML) and Artificial Intelligence (AI) architectures and use cases in support of ...

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Contract Machine Learning Software Engineer information

What is a contract machine learning software engineer?

A Contract Machine Learning Software Engineer is a professional who is hired on a temporary or project basis to design, develop, and deploy machine learning models and systems. They often work with organizations that need specialized expertise for a limited duration, helping to build algorithms, analyze data, and integrate AI solutions into existing software products. Contract engineers typically have strong backgrounds in programming, mathematics, and data science, and they may work remotely or on-site. Their responsibilities can range from data preprocessing and model training to deploying models in production environments. This arrangement allows companies to access advanced machine learning skills without committing to a full-time hire.

What are the key skills and qualifications needed to thrive as a contract machine learning software engineer?

To thrive as a Contract Machine Learning Software Engineer, you need a strong background in computer science, proficiency in programming languages like Python, and expertise in machine learning algorithms, typically supported by a relevant degree or equivalent experience. Familiarity with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, along with knowledge of version control systems like Git, is essential. Strong problem-solving abilities, communication skills, and the ability to work independently or with cross-functional teams make someone stand out in this role. These skills ensure efficient delivery of scalable machine learning solutions that meet client requirements and project timelines.

How does a contract machine learning software engineer typically collaborate with full-time team members during a project?

As a Contract Machine Learning Software Engineer, you will often work closely with full-time data scientists, software engineers, and product managers. Collaboration usually happens through regular stand-up meetings, code reviews, and shared documentation platforms. Despite being a contractor, you’re expected to integrate seamlessly with the team, communicate progress transparently, and adapt to the company’s workflows. Building strong relationships and proactively seeking feedback can help ensure your contributions align with the project’s goals and timelines.

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

AspectContract Machine Learning Software EngineerData Scientist
CredentialsBachelor's or Master’s in CS, ML, or related fields; experience with ML frameworksBachelor's or Master’s in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentProject-based, often remote, focused on developing ML models and softwareData analysis, visualization, and interpretation, often in research or business settings
Employer & Industry UsageTech companies, startups, consulting firms; used for deploying ML solutionsResearch institutions, finance, healthcare, and tech; used for insights and decision-making

The main difference is that Contract Machine Learning Software Engineers focus on developing and deploying ML models as software solutions, while Data Scientists analyze data to generate insights. Both roles require strong technical skills, but their primary objectives and work environments differ.

What are the most commonly searched types of Machine Learning Software Engineer jobs in Alabama?

The most popular types of Machine Learning Software Engineer jobs in Alabama are:

What are popular job titles related to Contract Machine Learning Software Engineer jobs in Alabama?

For Contract Machine Learning Software Engineer jobs in Alabama, the most frequently searched job titles are:

What job categories do people searching Contract Machine Learning Software Engineer jobs in Alabama look for?

The top searched job categories for Contract Machine Learning Software Engineer jobs in Alabama are:

What cities in Alabama are hiring for Contract Machine Learning Software Engineer jobs?

Cities in Alabama with the most Contract Machine Learning Software Engineer job openings:

Contract Machine Learning Software Engineer jobs near you
Infographic showing various Contract Machine Learning Software Engineer job openings in Alabama as of August 2026, with employment types broken down into 92% Full Time, and 8% Temporary. Highlights an 92% In-person, and 8% Remote job distribution.

Machine Learning Engineer

Astrion

Huntsville, AL • On-site

Full-time

Re-posted 8 days ago

Job description

Overview
Machine Learning Engineer
JOB LOCATION: Huntsville, Al
JOB STATUS: Full-time
CLEARANCE: TS/SCI w CI/Poly
TRAVEL: As needed
Astrion seeking a Machine Learning Engineer to join our analytics team working on an innovative MLOps workload leveraging cutting-edge technologies and supporting a government customer in Huntsville, Alabama.
This role will be responsible for delivering automation to key national security missions interacting with petabyte-scale data on supercomputing resources.
The ideal candidate will have a background in AI/ML model development and deployment and have experience in Python programming, handling SQL databases, and working in command line interfaces.
The team will work with technologies including:
  • Open source, commercial, and government software packages such as Docker, Python, Jupiter Notebooks, PostgreSQL, and other tools.
  • Leverage GitOps patterns and CI/CD with tools like GitLab and GitHub.

Work Environment
  • Working conditions are normal for an office environment.
  • Fast paced, deadline-oriented environment.
  • May require periods of non-traditional working hours including consecutive nights or weekends (if applicable).

REQUIRED QUALIFICATIONS / SKILLS
  • TS/SCI with CI Polygraph
  • 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 / SKILLS
  • Experience with petabyte scale data sets
  • Experience with multi-INT analytics
  • Experience deploying, monitoring, and scaling models in production environments

RESPONSIBILITIES
  • 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.

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