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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 ...

Machine Learning Engineer

Atlanta, GA · On-site

$62K - $100K/yr

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

Machine Learning Engineer

Alpharetta, GA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... the machine learning function at a market-leading insurance company. As one of the first data ... Leverage continuous engineering practices to deliver business value regarding effectiveness of the ...

Senior Machine Learning Engineer

Atlanta, GA · On-site

$100K - $138K/yr

  • Medical

  • Life

  • Retirement

  • PTO

Senior Machine Learning Engineer Team: Data & Audience Platform (DAP) - ML Engineering What We Do Warner Bros. Discovery (WBD) is home to the world's most iconic entertainment, news, and sports ...

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$220K - $280K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

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

$220K - $280K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

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 ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

Showing results 21-40

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 Aug 18, 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 is a 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 projects can a Machine Learning Engineer I 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 are the key skills and qualifications needed to thrive as a Machine Learning Engineer I?

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.

Infographic showing various Machine Learning Engineer I job openings in Georgia as of August 2026, with employment types broken down into 1% As Needed, 69% Full Time, 21% Part Time, 6% Contract, and 3% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $108,730 per year, or $52.3 per hour.

Machine Learning Engineer

Bespoke Labs

Lawrenceville, GA • On-site

Full-time

Re-posted 2 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