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Freelance Machine Learning Engineer Jobs in Alabama

Machine Learning Engineer

Huntsville, AL ยท On-site

$135K - $150K/yr

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 ...

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 ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

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Freelance Machine Learning Engineer information

See Alabama salary details

$13

$43

$119

How much do freelance machine learning engineer jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for freelance machine learning engineer in Alabama is $43.24, according to ZipRecruiter salary data. Most workers in this role earn between $22.02 and $56.01 per hour, depending on experience, location, and employer.

What does a freelance machine learning engineer do?

A Freelance Machine Learning Engineer designs, develops, and implements machine learning models and algorithms for clients on a project basis. They work independently to analyze data, build predictive models, and help businesses solve complex problems using AI and machine learning techniques. Their responsibilities may also include data preprocessing, model evaluation, and deploying solutions into production environments. Freelance Machine Learning Engineers often collaborate remotely with teams and must manage their own schedules and client relationships.

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

To thrive as a Freelance Machine Learning Engineer, you need expertise in programming (especially Python), a solid grasp of machine learning algorithms, and a relevant academic background such as a degree in computer science, mathematics, or engineering. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (AWS, GCP, Azure), and experience with version control systems are typically required. Strong problem-solving, self-management, and client communication skills help set successful freelancers apart. These competencies are crucial for delivering effective solutions, managing projects independently, and building client trust in a competitive market.

How do freelance machine learning engineers typically manage client expectations and project scopes?

Freelance machine learning engineers often work with clients who may not have a deep technical understanding of AI or data science. A common challenge is clearly defining the project scope and deliverables at the outset, ensuring both parties understand what is feasible given the data, time, and budget constraints. Successful freelancers use regular progress updates, milestone-based deliverables, and transparent communication to manage expectations and avoid scope creep. Building trust through clear documentation and setting realistic timelines also helps foster long-term client relationships.

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

AspectFreelance Machine Learning EngineerData Scientist
CredentialsTypically requires a degree in computer science, data science, or related fields; certifications in machine learning or AI are a plusUsually holds a degree in statistics, data science, or related areas; certifications in data analysis or visualization are common
Work EnvironmentIndependent, project-based work often remotely for various clientsOften employed full-time in organizations or consulting roles, sometimes freelance
Industry UsageUsed across tech, finance, healthcare, and startups for deploying ML modelsApplied in research, analytics, and strategic decision-making across industries

Freelance Machine Learning Engineers focus on developing and deploying ML models independently for diverse clients, while Data Scientists analyze data to extract insights, often working within organizations. Both roles require strong technical skills, but their work scope and environment differ significantly.

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

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

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

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

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

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

Infographic showing various Freelance Machine Learning Engineer job openings in Alabama as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $89,941 per year, or $43.2 per hour.

Machine Learning Engineer

Astrion

Huntsville, AL โ€ข On-site

$135K - $150K/yr

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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