1

Machine Learning Engineer I Jobs in Georgia (NOW HIRING)

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Senior Machine Learning Engineer

Atlanta, GA · On-site

$117K - $155K/yr

The Senior Machine Learning Engineer will design, train, and deploy machine learning models, collaborating with various business units to improve clinical and operational outcomes at scale.

Senior Machine Learning Engineer

Atlanta, GA · On-site +1

$117K - $155K/yr

The Senior Full-Stack Machine Learning Engineer sits within the Insights Business Unit, which ... Sedentary work (i.e., sitting for long periods of time). * Exerting up to 10 pounds of force ...

Senior Machine Learning Engineer

Atlanta, GA · On-site

$117K - $155K/yr

The Senior Machine Learning Engineer will contribute to both classical machine learning and generative AI applications, working across the full model development lifecycle on a modern, cloud-native ...

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$220K - $280K/yr

As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize our core machine learning capabilities. Your work will directly impact key metrics like Time-to-Bet ...

... Machine Learning Engineer to support advanced analytics and data science initiatives at Fort ... IAM Level I certification * Experience with high-performance computing environments * Experience ...

As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize our core machine learning capabilities. Your work will directly impact key metrics like Time-to-Bet ...

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$220K - $280K/yr

As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize our core machine learning capabilities. Your work will directly impact key metrics like Time-to-Bet ...

next page

Showing results 1-20

Machine Learning Engineer I information

See Georgia salary details

$26.6K

$108.7K

$163.4K

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

As of Jun 22, 2026, the average yearly pay for machine learning engineer i in Georgia is $108,730.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,700.00 and $130,900.00 per year, depending on experience, location, and employer.

What are Machine Learning Engineer I?

A Machine Learning Engineer I is an entry-level professional who designs, builds, and deploys machine learning models within software applications. They work closely with data scientists and software developers to implement algorithms that allow computers to learn from data and make predictions or decisions. Typical responsibilities include cleaning and preparing data, training models, evaluating performance, and optimizing algorithms for scalability and efficiency. This role often requires knowledge of programming languages like Python, frameworks such as TensorFlow or PyTorch, and a solid understanding of statistics and machine learning principles.

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

To thrive as a Machine Learning Engineer I, you need a solid foundation in programming (especially Python), mathematics, and machine learning concepts, typically supported by a bachelor’s degree in computer science or a related field. Familiarity with frameworks like TensorFlow or PyTorch, version control systems (e.g., Git), and cloud platforms is often expected. Strong problem-solving abilities, teamwork, and effective communication help you collaborate with stakeholders and translate business needs into technical solutions. These skills are crucial for building robust models, integrating them into production environments, and driving impactful results in data-driven projects.

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

AspectMachine Learning Engineer IData Scientist
Required CredentialsBachelor's in CS, Math, or related field; some roles may prefer certifications in ML or data analysisBachelor's or higher in Statistics, Data Science, or related field; often requires knowledge of programming and statistics
Work EnvironmentDevelops, tests, and deploys ML models; collaborates with data engineers and software developersAnalyzes data, builds models, and provides insights; works closely with business teams and analysts
Employer & Industry UsageTech companies, startups, and industries implementing AI solutionsFinance, healthcare, marketing, and research sectors relying on data-driven decisions

Machine Learning Engineer I focuses on developing and deploying ML models, while Data Scientists analyze data to generate insights. Both roles require programming skills and a background in math or statistics, but their daily tasks and objectives differ slightly.

What are the typical projects a Machine Learning Engineer I can expect to work on during their first year?

As a Machine Learning Engineer I, you can expect to work on projects such as data preprocessing, building and testing basic machine learning models, and implementing existing algorithms under the guidance of senior team members. You'll often collaborate with data scientists, software engineers, and product managers to translate business requirements into technical solutions. Early projects may also involve model evaluation, feature engineering, and helping to deploy models into production environments. This hands-on experience helps build a strong foundation for tackling more complex problems as you advance in your career.
What job categories do people searching Machine Learning Engineer I jobs in Georgia look for? The top searched job categories for Machine Learning Engineer I jobs in Georgia are:

Machine Learning Engineer

Bespoke Labs

Valdosta, GA • On-site

Full-time

This job post has expired today. Applications are no longer accepted.


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