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Remote Reinforcement Learning Intern Jobs in Atlanta, GA

PrizePicks

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$220K - $280K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Experience implementing reinforcement learning or complex probabilistic models for dynamic pricing ... S. and are willing to consider remote candidates. #LI-Remote Working at PrizePicks: The typical ...

Tier4 Group

Marketing Internship

Alpharetta, GA · Remote

$14.25 - $19/hr

Remote (Atlanta-based preferred for event support) Time Commitment: 3-8 hours/week (flexible ... The TAG CX Society is looking for a creative, self-driven intern to support our Marketing ...

Crowe LLP

Tax Intern Winter 2027

Atlanta, GA · On-site +1

$27 - $42/hr

Learning foundations of tax concepts needed as a tax professional * In addition, staff may have ... Candidates who are not within commuting distance of a Crowe office may be considered for a remote ...

Finastra

Expert Functional Consultant, Loan IQ

Atlanta, GA · On-site +1

  • Medical

  • Life

  • Retirement

  • PTO

... or reinforcement of training, and implementation support of software applications for new and ... Provide on-site or remote support during client conversions as applicable. * Establish and/or ...

All JobsReinforcement Learning Intern JobsRemote Reinforcement Learning Intern JobsRemote Reinforcement Learning Intern Jobs in Atlanta, GA

Remote Reinforcement Learning Intern information

See Atlanta, GA salary details

$8

$16

$23

How much do remote reinforcement learning intern jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for remote reinforcement learning intern in Atlanta, GA is $16.38, according to ZipRecruiter salary data. Most workers in this role earn between $13.85 and $18.51 per hour, depending on experience, location, and employer.

What does a remote reinforcement learning intern do?

A Remote Reinforcement Learning Intern assists with research and development projects that focus on reinforcement learning, a type of machine learning where agents learn to make decisions by trial and error. Their tasks often include implementing algorithms, running experiments, analyzing results, and contributing to academic papers or practical applications. Working remotely, they collaborate with teams using online tools and communicate progress regularly. The role is ideal for students or recent graduates who want to gain hands-on experience in artificial intelligence and machine learning.

What are common challenges faced by remote reinforcement learning interns, and how can they be overcome?

Remote reinforcement learning interns often encounter challenges related to communication and collaboration, especially when working with distributed teams. It can also be difficult to access computational resources or receive timely feedback on experiments. To overcome these challenges, it's important to proactively schedule regular check-ins with mentors, utilize collaborative tools (such as Slack or GitHub), and ensure a reliable internet connection. Additionally, keeping detailed documentation and being transparent about progress can help facilitate smoother teamwork and problem-solving.

What skills and qualifications are needed to thrive as a remote reinforcement learning intern?

To thrive as a Remote Reinforcement Learning Intern, you need a strong background in mathematics, programming (especially Python), and foundational knowledge of machine learning concepts, typically demonstrated through coursework or relevant projects. Familiarity with reinforcement learning libraries (such as TensorFlow, PyTorch, or OpenAI Gym), version control systems like Git, and possibly cloud computing platforms is highly valuable. Excellent problem-solving abilities, self-motivation, and effective remote communication skills help interns excel in independent and collaborative tasks. These skills are essential for contributing to innovative research and development projects while working efficiently in a distributed team environment.
What are popular job titles related to Remote Reinforcement Learning Intern jobs in Atlanta, GA? For Remote Reinforcement Learning Intern jobs in Atlanta, GA, the most frequently searched job titles are:
What job categories do people searching Remote Reinforcement Learning Intern jobs in Atlanta, GA look for? The top searched job categories for Remote Reinforcement Learning Intern jobs in Atlanta, GA are:
Remote Reinforcement Learning Intern jobs near you
Infographic showing various Remote Reinforcement Learning Intern job openings in Atlanta, GA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 21% Part Time, 1% Temporary, and 4% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution, with an average salary of $34,077 per year, or $16.4 per hour.

Staff Machine Learning Engineer

PrizePicks

Atlanta, GA • On-site, Remote

$220K - $280K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 7 days ago

Job description

At PrizePicks, we are the fastest-growing sports company in North America, as recognized by Inc. 5000. As the leading platform for Daily Fantasy Sports, we cover a diverse range of sports leagues, including the NFL, NBA, and Esports titles like League of Legends and Counter-Strike. Our team of over 550 employees thrives in an inclusive culture that values individuals from diverse backgrounds, regardless of their level of sports fandom. Ready to reimagine the DFS industry together?
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, Deposit Velocity, and Platform Integrity by integrating robust, low-latency ML models across our sports betting and daily fantasy ecosystems.
What you'll do:
  • Architect Scalable ML Systems: Design and build the end-to-end machine learning infrastructure, transitioning experimental Data Science models into robust, high-availability production services.
  • Real-Time Inference at Scale: Steer the design and deployment of low-latency services to serve model inferences in milliseconds. You will power real-time decisions across the platform, from dynamic oddsmaking and risk analysis to smart deposit defaults.
  • Feature Engineering & Data Strategy: Partner with Data Science to build scalable logging and data pipelines. You will lead the creation and optimization of a centralized feature store required to train complex models across diverse business domains.
  • End-to-End MLOps Leadership: Champion best practices for model deployment, monitoring, and CI/CD for ML. You will implement automated retraining pipelines and observability tools to ensure data drift and model degradation are caught and addressed instantly.
What you have:
  • 7+ years of experience in Machine Learning Engineering or Backend Engineering, with a proven track record of deploying and maintaining complex ML models in high-traffic production environments.
  • 3+ years of technical leadership, acting as a lead and driving architecture decisions for consumer applications or scalable backend platforms.
  • Experience with Real-Time Data: Proficient in streaming architectures (Kafka/Flink/PubSub) and building low-latency services to serve model inference in <100ms.
  • MLOps Expertise: Deep experience managing the full ML lifecycle (training, deploying, monitoring) using tools like MLFlow, Kubeflow, Databricks, or SageMaker.
  • Strong Coding Skills: Expert in Python and SQL; proficiency in Go, C++, or Rust is a strong plus for building high-performance inference layers.
  • Cloud Native: Deep experience with GCP services (BigQuery, Cloud Functions, GKE, Vertex AI) or AWS equivalents.
What makes you stand out:
  • Experience implementing reinforcement learning or complex probabilistic models for dynamic pricing, risk management, or fraud detection.
  • Background in Daily Fantasy Sports (DFS), oddsmaking, or high-frequency trading.
  • Experience building and scaling "Feature Stores" that successfully bridge batch historical data with real-time event streams.
Where you'll live:
  • While we prefer candidates based in Atlanta, we are open to qualified applicants from anywhere in the U.S. and are willing to consider remote candidates. #LI-Remote
Working at PrizePicks:
The typical salary range for this position is $220,000 to $280,000. At PrizePicks, we consider your role, level, and where you'll be working when determining our salary ranges. The compensation info you see on our job postings gives you an idea of the starting pay range for the position. Your actual pay within that range will depend on your specific work location, as well as your skills, experience, and education. Your recruiter will be happy to chat more about the specific pay range for your location and how we arrived at it during the hiring process.
This application period will remain open for 30 days. We're committed to finding the best candidate, so this date may be adjusted, and any changes will be reflected in this posting.
Date Posted: 4/16/2026
1st Extension: 5/16/2026
2nd Extension: 6/16/2026
Benefits you'll receive:
In addition to your great compensation package, full-time employees will be eligible for the following perks:
  • Company-subsidized medical, dental, & vision plans
  • 401(k) plan with company match
  • Annual bonus
  • Flexible PTO to encourage a healthy work/life balance (2 weeks STRONGLY encouraged!)
  • Generous paid leave programs, including 16-week paid parental leave and disability benefits
  • Workplace flexibility and modern work schedules focused on getting the job done, not hours clocked
  • Company-wide in-person events and team outings
  • Lifestyle enhancement program
  • Company equipment provided (Windows & Mac options)
  • Annual performance reviews with opportunities for growth and career development

You must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.
PrizePicks is an Equal Opportunity Employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

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