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Machine Learning Research Engineer Jobs in Alabama

Whiterabbit.ai

Learn and understand a large body of research in deep learning and machine learning * Participate in cutting-edge research for medical applications of computer vision Must Have Experience

New

Whiterabbit.ai

Learn and understand a large body of research in deep learning and machine learning * Participate in cutting-edge research for medical applications of computer vision Must Have Experience

New

Whiterabbit.ai

Learn and understand a large body of research in deep learning and machine learning * Participate in cutting-edge research for medical applications of computer vision Must Have Experience

New

Bespoke Labs

Machine Learning Engineer

Mobile, AL · On-site

About Us We are AI researchers and builders who understand how to curate data and RL environments ... Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ...

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All JobsMachine Learning Research Engineer JobsMachine Learning Research Engineer Jobs in Alabama

Machine Learning Research Engineer information

See Alabama salary details

$33.5K

$96.1K

$129.2K

How much do machine learning research engineer jobs pay per year?

As of Jul 17, 2026, the average yearly pay for machine learning research engineer in Alabama is $96,088.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,300.00 and $94,300.00 per year, depending on experience, location, and employer.

What does a machine learning research engineer do?

A machine learning research engineer develops and improves algorithms and models that enable computers to learn from data. They often work on creating new techniques, testing prototypes, and publishing findings, using tools like Python, TensorFlow, or PyTorch. Their work supports advancing AI capabilities and typically requires strong programming, statistical, and mathematical skills.

How much do ML research engineers make?

Machine Learning Research Engineers typically earn between $90,000 and $150,000 annually, with salaries increasing based on experience, education, and location. Senior roles or those with specialized skills in deep learning, NLP, or computer vision can earn over $200,000. Compensation often includes benefits such as bonuses, stock options, and professional development opportunities.

What does a Machine Learning Research Engineer do?

A Machine Learning Research Engineer develops and improves machine learning models, conducts research to advance AI techniques, and implements scalable algorithms. They work at the intersection of applied research and engineering, leveraging mathematical and statistical methods to optimize performance. Their role involves experimenting with new architectures, analyzing large datasets, and collaborating with data scientists and software engineers to deploy models into production.

What are some common challenges faced by Machine Learning Research Engineers in their daily work?

Machine Learning Research Engineers often encounter challenges such as sourcing and preparing large, high-quality datasets, tuning complex model architectures, and ensuring reproducibility of experimental results. They work closely with cross-functional teams, including data scientists and software engineers, to deploy models in production environments and must frequently adapt to rapidly evolving research. Keeping up with the latest scientific literature and integrating new algorithms into ongoing projects can be demanding but is also rewarding. This collaborative, fast-paced environment provides constant opportunities for learning and professional development.

What are the key skills and qualifications needed to thrive in the Machine Learning Research Engineer position, and why are they important?

A Machine Learning Research Engineer typically needs a strong background in computer science, mathematics, and statistics, often with a graduate degree in a related field. Proficiency in programming languages such as Python or C++, experience with machine learning frameworks like TensorFlow or PyTorch, and familiarity with tools for data analysis are crucial, along with relevant certifications being a plus. Strong problem-solving skills, collaboration, and effective communication help drive innovative research and facilitate teamwork. These competencies are essential for developing advanced machine learning models, staying current with evolving technologies, and effectively translating research into real-world applications.

What engineers make $500,000?

Senior machine learning research 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 engineers make $300,000 a year?

Senior machine learning research engineers with extensive experience, advanced skills in deep learning and data science, and often a strong publication record can earn $300,000 or more annually. Compensation varies based on industry, location, company size, and individual expertise, with roles in tech giants and finance firms typically offering higher salaries.
What are popular job titles related to Machine Learning Research Engineer jobs in Alabama? For Machine Learning Research Engineer jobs in Alabama, the most frequently searched job titles are:
What job categories do people searching Machine Learning Research Engineer jobs in Alabama look for? The top searched job categories for Machine Learning Research Engineer jobs in Alabama are:
Machine Learning Research Engineer jobs near you

Machine Learning Engineer

Waypoint Human Capital

Huntsville, AL • On-site

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Position Title: Machine Learning Engineer
Position Type: Full-time, On-Site
Location: Huntsville, AL
Clearance: Active TS
Description:
Waypoint’s client is seeking a Machine Learning Engineer to support mission-critical efforts within a secure environment at the Missile and Space Intelligence Center. This role focuses on developing, integrating, and operationalizing machine learning solutions that support advanced analytics and intelligence capabilities.
The selected candidate will work across the full machine learning lifecycle, from building data pipelines and training models to deploying and monitoring production systems. This position requires a strong blend of software engineering and data science expertise, with a focus on scalability, performance, and system integration.
Responsibilities:
• Integrate machine learning systems into existing software architectures and enterprise platforms
• Design, build, and optimize data pipelines to support model training and inference
• Develop, test, and deploy machine learning models into production environments
• Manage transition from prototype to production, including deployment pipelines and monitoring solutions
• Monitor model performance, including handling model drift, rollback, and failure scenarios
• Conduct experiments and testing to evaluate and improve model accuracy and performance
• Write clean, maintainable, and testable code in Python and related technologies
• Collaborate with cross-functional teams to integrate ML capabilities into mission systems
• Utilize CI/CD pipelines and GitOps practices to support automated deployment and version control
• Support development in Linux and Windows environments
Required:
• Active TS clearance (with ability to obtain TS/SCI with CI Polygraph)
• Bachelor’s degree in Computer Science, Mathematics, Statistics, Physics, or related technical field
• Minimum 12+ years of overall experience, including 1–3 years working with machine learning frameworks
• Strong programming skills in Python
• Experience with machine learning frameworks, libraries, and data modeling techniques
• Solid understanding of the machine learning lifecycle
• Experience working with SQL and NoSQL databases
• Experience working in Linux and Windows environments
• Familiarity with CI/CD pipelines and Agile development methodologies
• Understanding of software design and system integration principles
Desired:
• Active TS/SCI with CI Polygraph (desired)
• Experience working with large-scale (petabyte-level) datasets
• Experience supporting multi-INT analytics environments
• Experience deploying, monitoring, and scaling machine learning models in production
• Experience with tools such as Docker, Jupyter Notebooks, PostgreSQL, GitLab, and GitHub
• Experience implementing GitOps workflows
• Experience working in secure or classified environment