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Machine Learning Research Engineer Jobs in Alabama

Bespoke Labs

Machine Learning Engineer

Mobile, AL

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 ...

Bespoke Labs

Machine Learning Engineer

Montgomery, 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 ...

Bespoke Labs

Machine Learning Engineer

Birmingham, 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 ...

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 ...

Astrion

Mid-level Machine Learning Engineer

Huntsville, AL · 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 ...

Quora

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning systems, building performant and reliable LLM applications and collaborating with our product team to ...

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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 Aug 7, 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 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 as a machine learning research engineer?

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 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
Infographic showing various Machine Learning Research Engineer job openings in Alabama as of July 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $96,088 per year, or $46.2 per hour.

Machine Learning Engineer

Bespoke Labs

Mobile, AL

Full-time

Re-posted 20 days ago

Job description

About Us

We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.

We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.

What You'll Be Working On

You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.

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 preferred; familiar with training loops, optimizers, mixed precision)

Hands-on experience with LLM post-training — SFT, RLHF, PPO, DPO, or reward model training — and understanding of how training data quality affects model behavior

Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives

Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)

Solid understanding of evaluation methodology — held-out sets, benchmark design, avoiding train/eval contamination

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