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Reinforcement Learning Jobs in Georgia (NOW HIRING)

Intuit

Senior Staff AI Scientist

Atlanta, GA · On-site

Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and ...

Kiongroup

AI Scientist

Atlanta, GA

$98K - $123K/yr

Experience with reinforcement learning and/or large language models (LLMs), including LLM-based applications * Interest in applied AI within supply chain, logistics, or industrial automation Location ...

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Reinforcement Learning information

See Georgia salary details

$24.1K

$49.3K

$67.6K

How much do reinforcement learning jobs pay per year?

As of Jun 13, 2026, the average yearly pay for reinforcement learning in Georgia is $49,267.00, according to ZipRecruiter salary data. Most workers in this role earn between $42,600.00 and $57,400.00 per year, depending on experience, location, and employer.

What are the common responsibilities of a Reinforcement Learning professional on a daily basis?

A typical day for a Reinforcement Learning professional involves designing and implementing learning algorithms, running experiments, analyzing data, and iterating on models to improve performance. You might collaborate closely with data scientists, software engineers, and product managers to integrate your solutions into broader systems or products. Regular activities also include reading recent research literature and participating in team meetings to discuss progress and obstacles. This dynamic role often balances deep technical work with teamwork to drive innovative applications in areas such as robotics, recommendation systems, or autonomous systems.

Who earns more, AI or ML engineer?

Reinforcement Learning engineers, a specialized subset of AI and ML engineers, tend to earn higher salaries due to their advanced skills in developing algorithms for decision-making systems. Overall, AI engineers generally have higher average salaries than ML engineers, but salaries vary based on experience, location, and industry. Both roles require strong programming skills and knowledge of machine learning frameworks.

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

To thrive in a Reinforcement Learning role, you need a solid background in mathematics, statistics, machine learning, and programming (commonly with Python), typically supported by a relevant degree such as in computer science or engineering. Experience with frameworks like TensorFlow, PyTorch, OpenAI Gym, and familiarity with large-scale computing systems are highly valued. Strong problem-solving abilities, curiosity, and effective collaboration and communication skills help you excel in multidisciplinary research and project teams. These capabilities are crucial for designing, implementing, and refining complex algorithms that learn from interaction to solve real-world problems.

What engineers make $500,000?

Senior reinforcement learning engineers with extensive experience, advanced skills in machine learning frameworks, and a strong track record in deploying AI systems can earn salaries approaching or exceeding $500,000, especially in high-cost-of-living areas or within leading tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their specialized expertise and impact on product development.

Which 5 jobs will survive AI?

Reinforcement Learning specialists, data scientists, AI researchers, software engineers, and cybersecurity analysts are likely to continue thriving as AI advances, due to their expertise in developing, managing, and securing AI systems. These roles require advanced technical skills, problem-solving abilities, and ongoing learning to adapt to evolving technologies.

What is a Reinforcement Learning job?

A Reinforcement Learning (RL) job involves designing, developing, and optimizing algorithms that enable machines to learn from interactions with their environment. RL professionals work on applications in robotics, finance, gaming, and autonomous systems, leveraging techniques like deep reinforcement learning and policy optimization. Responsibilities often include researching new models, implementing RL algorithms, and improving AI performance. Strong programming skills, knowledge of machine learning frameworks, and an understanding of mathematical concepts like probability and optimization are essential.

Which 3 jobs will survive AI?

Reinforcement Learning specialists, data scientists, and AI ethics professionals are likely to remain in demand as AI advances, due to their specialized skills in developing, managing, and overseeing AI systems. These roles require advanced knowledge of algorithms, programming, and ethical considerations, making them less susceptible to automation. Continuous learning and expertise in AI tools and frameworks help ensure job security in this evolving field.
What are the most commonly searched types of Reinforcement Learning jobs in Georgia? The most popular types of Reinforcement Learning jobs in Georgia are:
What are popular job titles related to Reinforcement Learning jobs in Georgia? For Reinforcement Learning jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Reinforcement Learning jobs in Georgia look for? The top searched job categories for Reinforcement Learning jobs in Georgia are:
What cities in Georgia are hiring for Reinforcement Learning jobs? Cities in Georgia with the most Reinforcement Learning job openings:
Reinforcement Learning jobs near you
Infographic showing various Reinforcement Learning job openings in Georgia as of June 2026, with employment types broken down into 100% Part Time. Highlights an 100% In-person job distribution, with an average salary of $49,267 per year, or $23.7 per hour.
Senior Staff AI Scientist

Senior Staff AI Scientist

Intuit

Atlanta, GA • On-site

Full-time

Posted 17 days ago

Intuit rating

8.3

Company rating: 8.3 out of 10

Based on 82 frontline employees who took The Breakroom Quiz

73rd of 189 rated software companies

Job description

Intuit is looking for innovative and hands-on Senior Staff AI Scientist to join the Intuit AI team.
Come join our collaborative and creative group of AI scientists and machine learning engineers and build models that directly affect hundreds of thousands of our customers. In this role you will be building and deploying machine learning models using both analytical algorithms and deep learning approaches.
Responsibilities
  • Practices leadership and communication skills to influence teams and to evangelize AI science across the organization
  • Collaborates with stakeholders to define success criteria and align model metrics with business goals. Works side-by-side with product managers, software engineers, and designers in designing experiments and minimum viable products
  • Leads technical work of a scrum team: initiating and designing model solutions, driving end-to-end architecture designs of the team's work, and holding the team accountable for high quality code, git, design, costs and implementation standards
  • Performs hands-on data analysis and modeling with large data sets, including discovering data sources, getting data access, cleaning up data, and making them "model-ready". You need to be willing and able to do your own ETL and design/build featurization.
  • Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and datasets.
  • Runs A/B tests to draw conclusions on the impact of your team's work and communicates results to peers and leaders
  • Communicates with partners to ensure successful delivery and integration of DS solutions.
  • Proactively researches, explores, and enables new ML technologies. Keeps up with the new developments in academia and industry and considers possible extensions to solve Intuit customer problems.

Qualifications
  • 6+ years of industry experience with AI science
  • BS, MS or PhD in Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent
  • 4+ years of hands-on expertise in ML paradigms such as Causal-ML, supervised/unsupervised, Online, Bayesian, Reinforcement or Deep Learning.
  • Proficient in multiple optimization paradigms such as combinatorial optimization, gradient methods, or Bayesian optimization.
  • Proficient in NLP techniques, Explainable AI, and ML frameworks.
  • Expertise in modern advanced analytical tools and programming languages such as Python, Scala, Java and/or R.
  • Efficient in SQL, Hive, SparkSQL, etc.
  • Comfortable working in a Linux environment
  • Experience with building end-to-end reusable pipelines from data acquisition to model output delivery
  • Quick learner, adaptable, with the ability to work independently in a fast-paced environment
  • Strong oral and written communication skills. Ability to conduct meetings and make professional presentations, and to explain complex concepts and technical material to non-technical users

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at ). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is:

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