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Postdoctoral In Reinforcement Learning Jobs in Austell, GA

Intuit

AI Scientist 2

Atlanta, GA · On-site

... in partnership with machine learning engineers and guided by senior scientists. * Apply various machine learning techniques (supervised, unsupervised, reinforcement learning, NLP, GenAI) to improve ...

Emory University

Postdoctoral Fellow- LUMeN Lab

Atlanta, GA · On-site

$47K - $64K/yr

... Learning, Understanding, Memory, & Neurodevelopment Lab (LUMeN Lab, PI: Dr. Alexandra Cohen) in the ... Postdoctoral Fellow to work on NIH-funded studies examining emotion-related learning, memory, and ...

Emory University

Postdoctoral Fellow- LUMeN Lab

Atlanta, GA · On-site

$47K - $64K/yr

... Learning, Understanding, Memory, & Neurodevelopment Lab (LUMeN Lab, PI: Dr. Alexandra Cohen) in the ... Postdoctoral Fellow to work on NIH-funded studies examining emotion-related learning, memory, and ...

AT&T

Senior Data Scientist

Atlanta, GA · On-site

Proficiency in algorithm categories such as Supervised Learning, Unsupervised Learning, Optimization Algorithms, Deep Learning, AI-Computer Vision, Natural Language Processing, Deep Reinforcement ...

AIG

Ph.D. Research Data Scientist, GenAI

Atlanta, GA · On-site

... in agentic AI, reinforcement learning, and reasoning into practical solutions that support underwriting, Operation, claims automation, customer servicing, and risk assessment • Experience ...

Waystar, Inc

Senior ML Engineer II

Atlanta, GA · On-site

$120 - $160/hr

... reinforcement learning techniques, as well as deep learning architectures. Strong experience with cloud platforms (AWS, Azure, GCP) and their ML services. Proficiency in building and managing data ...

Intuit

Staff AI Scientist

Atlanta, GA

... based models, reinforcement learning, clustering, time series, causal analysis, and natural ... Proficiency in deep learning ML frameworks such as TensorFlow, PyTorch, etc. * Work experience with ...

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Postdoctoral In Reinforcement Learning information

See Austell, GA salary details

$22.9K

$54K

$76.4K

How much do postdoctoral in reinforcement learning jobs pay per year?

As of Aug 8, 2026, the average yearly pay for postdoctoral in reinforcement learning in Austell, GA is $54,017.00, according to ZipRecruiter salary data. Most workers in this role earn between $44,800.00 and $60,900.00 per year, depending on experience, location, and employer.

What is the difference between Postdoctoral In Reinforcement Learning vs Postdoctoral In Machine Learning?

AspectPostdoctoral In Reinforcement LearningPostdoctoral In Machine Learning
Required CredentialsPhD in Computer Science, AI, or related field; strong programming skills; research experience in reinforcement learningPhD in Computer Science, AI, or related field; strong programming skills; research experience in machine learning
Work EnvironmentAcademic labs, research institutions, industry R&D teams focused on reinforcement learning applicationsAcademic labs, research institutions, industry R&D teams working on various machine learning techniques
Industry UsagePrimarily in AI research, robotics, gaming, and autonomous systemsBroader applications including data analysis, predictive modeling, and AI research

Postdoctoral In Reinforcement Learning specializes in research related to decision-making algorithms and autonomous systems, whereas Postdoctoral In Machine Learning covers a wider range of AI techniques. Both roles require similar credentials but differ in focus and application areas.

What are the key skills and qualifications needed to thrive as a postdoctoral researcher in reinforcement learning?

To thrive as a Postdoctoral Researcher in Reinforcement Learning, you need a PhD in computer science or a related field, with deep expertise in machine learning, statistics, and algorithm development. Proficiency in programming languages such as Python, experience with deep learning frameworks (e.g., TensorFlow or PyTorch), and familiarity with reinforcement learning libraries are typically required. Strong analytical thinking, problem-solving ability, collaboration, and scientific communication skills help you excel in research teams and publish impactful work. These competencies are vital to advancing state-of-the-art research, developing novel algorithms, and contributing to the academic and industrial progress in AI.

What are some common challenges faced by postdoctoral researchers in reinforcement learning, and how can they be addressed?

Postdoctoral researchers in reinforcement learning often face challenges such as balancing independent research projects with collaborative work, staying up-to-date with rapidly evolving literature, and managing the pressure to publish in top conferences. Effective time management, regular engagement with the research community through seminars and workshops, and seeking mentorship from senior colleagues can help address these challenges. Additionally, collaborating with interdisciplinary teams can offer fresh perspectives and support, making it easier to navigate complex research problems.

What is a postdoctoral researcher in reinforcement learning?

A Postdoctoral Researcher in Reinforcement Learning is an individual who has completed a PhD and conducts advanced research in the field of reinforcement learning, a branch of artificial intelligence focused on how agents take actions in environments to maximize rewards. These researchers often work in academic, industrial, or governmental research settings, collaborating on projects that advance the theoretical foundations or practical applications of reinforcement learning. Their responsibilities may include designing experiments, developing algorithms, publishing papers, and mentoring graduate students.
Postdoctoral In Reinforcement Learning jobs near you
Infographic showing various Postdoctoral In Reinforcement Learning job openings in Austell, GA as of June 2026, with employment types broken down into 34% Full Time, 65% Part Time, and 1% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $54,017 per year, or $26 per hour.

AI Scientist 2

Intuit

Atlanta, GA • On-site

Full-time

Re-posted 23 hours ago

Intuit rating

8.4

Company rating: 8.4 out of 10

Based on 91 frontline employees who took The Breakroom Quiz

87th of 242 rated software companies

Job description

Overview

We are seeking an AI Scientist to work with our collaborative and creative group of scientists and engineers to design and implement the next generation AI and machine learning systems that will power our omnichannel marketing platform. In this role, you will develop and deploy modern machine learning and AI models directly in our core product to address key customer challenges. We are looking for someone passionate about the full model development lifecycle, eager to collaborate with product managers to shape innovative AI product experiences, and driven to make a significant impact on our customers.


Responsibilities


  • Explore, develop, and deploy machine learning models, contributing to the end-to-end ML lifecycle in partnership with machine learning engineers and guided by senior scientists.

  • Apply various machine learning techniques (supervised, unsupervised, reinforcement learning, NLP, GenAI) to improve relevance and personalization algorithms, with an emphasis on understanding and implementing solutions that support broader AI initiatives.

  • Collaborate with product managers, software engineers, and designers in designing experiments and minimum viable products, learning to integrate insights from advanced AI systems.

  • Discover, process, and train on huge data sets.

  • In partnership with product managers and analysts, run regular A/B tests, perform statistical analysis, draw conclusions on the impact of your models, and communicate results to peers and leaders.

  • Research and explore new technology shifts, particularly in generative AI and advanced ML, to understand their potential connection with customer benefits and inform ongoing AI strategy.


Qualifications


  • MS, or PhD in an appropriate technology field (Computer Science, Statistics, Applied Math, Operations Research, etc.) or equivalent work experience.

  • 1+ years of experience in modern AI/ML tools and proficient in Python and typical AI/ML libraries (e.g., TensorFlow, PyTorch, Keras). Familiarity with distributed computing frameworks (e.g., Spark, Ray) is a plus.

  • 1+ years of experience in machine learning techniques such as classification, regression, neural networks, large language models, recommender systems, natural language processing, clustering, anomaly detection, and computer vision. Understanding of MLOps principles and practices (e.g., version control, CI/CD for ML models) is a plus.

  • Familiar with the latest trends and applications of generative AI including agentic applications. 

  • Efficient in SQL

  • Comfortable in a Linux environment

  • Solid communication skills: Demonstrated ability to explain complex technical issues to both technical and non-technical audiences.


Footer

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may 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 Intuit®: Careers | Benefits). 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. 



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