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Internship Deep Reinforcement Learning Jobs in Georgia

AT&T

Senior Data Scientist

Atlanta, GA

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

Intuit

Staff AI Scientist

Atlanta, GA

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 ...

Intuit

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 ...

Intuit

Staff AI Scientist

Atlanta, GA

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 ...

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 ...

Intuit

Senior Staff AI Scientist

Atlanta, GA

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 ...

Intuit

Senior Staff AI Scientist

Atlanta, GA

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 ...

PrizePicks

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$220K - $280K/yr

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 ...

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Internship Deep Reinforcement Learning information

What types of projects or tasks can I expect to work on during a Deep Reinforcement Learning internship?

As a Deep Reinforcement Learning (DRL) intern, you'll typically work on projects involving the development, implementation, and evaluation of reinforcement learning algorithms. This might include tasks like training agents in simulated environments, tuning hyperparameters, analyzing performance metrics, and collaborating with team members to integrate DRL solutions into larger systems. You'll also likely spend time reading recent research papers, experimenting with frameworks such as TensorFlow or PyTorch, and presenting your findings to the research team. Collaboration with mentors and other interns is common, and you'll gain hands-on experience that prepares you for more advanced roles in AI research or engineering.

What is an internship in Deep Reinforcement Learning?

An internship in Deep Reinforcement Learning (DRL) is a temporary, hands-on position where interns learn and apply state-of-the-art machine learning algorithms that enable computers to learn decision-making tasks through trial and error. Interns typically work on projects involving neural networks, reward systems, and environments like games or simulations. These internships provide valuable experience with frameworks such as TensorFlow or PyTorch, and exposure to current research in artificial intelligence. The experience helps students or recent graduates build technical skills and prepare for careers in AI research or industry.

What are the key skills and qualifications needed to thrive as an Intern in Deep Reinforcement Learning, and why are they important?

To thrive as an Intern in Deep Reinforcement Learning, you need a solid background in mathematics (especially linear algebra, probability, and calculus), programming (Python), and foundational knowledge in machine learning principles, usually supported by ongoing or completed coursework in computer science or related fields. Familiarity with frameworks and tools such as TensorFlow, PyTorch, OpenAI Gym, and experience using version control systems like Git are typically required. Analytical thinking, curiosity, and effective communication are essential soft skills for collaborating on research problems and sharing complex findings. These skills and qualities are crucial for contributing to innovative projects and successfully navigating the challenges of cutting-edge AI research.

What is the difference between Internship Deep Reinforcement Learning vs Data Science Intern?

AspectInternship Deep Reinforcement LearningData Science Intern
Required SkillsMachine learning, programming (Python), reinforcement learning conceptsStatistics, data analysis, programming (Python/R), data visualization
Work EnvironmentResearch labs, AI companies, tech startupsBusiness analytics, tech firms, consulting agencies
Industry UsageAI research, robotics, autonomous systemsBusiness intelligence, marketing, finance

Internship Deep Reinforcement Learning focuses on developing algorithms that enable systems to learn through trial and error, often in AI research or robotics. Data Science Internships involve analyzing data to extract insights and support decision-making. While both roles require programming skills, reinforcement learning emphasizes AI-specific techniques, whereas data science centers on statistical analysis and data visualization.

What are the most commonly searched types of Deep Reinforcement Learning jobs in Georgia? The most popular types of Deep Reinforcement Learning jobs in Georgia are:
What are popular job titles related to Internship Deep Reinforcement Learning jobs in Georgia? For Internship Deep Reinforcement Learning jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Internship Deep Reinforcement Learning jobs in Georgia look for? The top searched job categories for Internship Deep Reinforcement Learning jobs in Georgia are:
What cities in Georgia are hiring for Internship Deep Reinforcement Learning jobs? Cities in Georgia with the most Internship Deep Reinforcement Learning job openings:
Internship Deep Reinforcement Learning jobs near you

Senior Data Scientist

AT&T

Atlanta, GA

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 16 days ago

AT&T rating

7.3

Company rating: 7.3 out of 10

Based on 725 frontline employees who took The Breakroom Quiz

59th of 96 rated telecommunications companies

Job description

This position requires office presence of a minimum of 5 days per week and is only located in the location(s) posted. No relocation is offered.

Overall Purpose: This role will co-own critical AI deliverables for AT&T Finance Operations, supporting Treasury/Payments, Billing Operations and Corporate Financial Planning deliverables. Significant experience with these partners, their KPIs, processes and business challenges is preferred.

You will translate business problems into actionable insights through a comprehensive workflow involving coding, data extraction, cleansing, feature engineering, exploratory data analysis, model creation and tuning, visualization, and deployment, leveraging statistical analysis, machine learning, and big data technologies to drive informed decision-making and innovation.

Key Roles and Responsibilities: Typical tasks may include, but are not limited to, the following:

  • Data Extraction and Preparation: Collect data from various structured and unstructured sources (datalakes, databases, data warehouses, on cloud, internal, external) and ensure its quality for analysis through cleaning and preprocessing. Designs, builds, and analyzes large (e.g. 100's of Terabytes or higher as technology advances) and complex data sets while thinking strategically about data use and data design. Tools can include

  • Coding Solutions, Algorithms and Feature Engineering: Create relevant features and conduct exploratory data analysis. Codes solutions following typical workflow; data extraction, cleansing, feature engineering, exploratory data analysis, model selection/creation, hyper-parameter tuning, model interpretation, model retraining, business process and/or system implementations, high level proof of concept and trials, visualization, deployment to production, post deployment ML ops monitoring/diagnosis/resolutions. Coding proficiency required in at least one data science language (Python, R, Scala, etc.), as well as expertise with modern ML packages and libraries (Spark, SciKitLearn, Pandas, PyTorch, TidyVerse, Tensorflow, Keras, Shiny, and/or AutoML tools).

  • Model Development, Deployment and Optimization: Build, evaluate, and optimize machine learning models through hyperparameter tuning. Implement models into production, continuously monitor their performance, and ensure they remain explainable and reliable to minimize model decay. Ability to develop custom Machine Learning (ML). Highly proficient in the full AI workflow such as (1) data extraction, cleansing, feature engineering, exploratory data analysis, model selection/creation, hyper-parameter tuning, model interpretation, model retraining and (2) Uses concepts like mlflow to log metrics. Well-versed in Interactive Development Environments (IDEs) such as Databricks Workspaces or Visual Studio Code. Proficiency in algorithm categories such as Supervised Learning, Unsupervised Learning, Optimization Algorithms, Deep Learning, AI-Computer Vision, Natural Language Processing, Deep Reinforcement Learning, Search Algorithms, and AI- Knowledge Graphs.

  • Visualization and Collaboration: Create visualizations and reports for stakeholders while working closely with cross-functional teams to align efforts with business objectives. Can utilize advanced coding methods to produce visualizations (e.g. ggplot, D3.js, etc.).

  • Generative AI: Develop and implement generative AI models, focusing on creating new content or augmenting existing data. Generative Models-Understanding of GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and Transformers. Fine-Tuning-Techniques for adapting pre-trained models to specific tasks using smaller, task-specific datasets. Agentics-Understanding of agentic architecture, concepts and optimization of solutions. Prompt Engineering-Crafting effective prompts to guide generative models in producing desired outputs. Retrieval-Augmented Generation (RAG)-Combining generative models with retrieval systems to enhance performance and relevance. Text Generation-Proficiency in using models like GPT-3/4 for generating human-like text. Image Generation-Familiarity with tools like DALL-E and Stable Diffusion for creating images from text descriptions.

Job Contribution: An experienced professional with advanced, interdisciplinary knowledge, resolving difficult and complex issues using broad professional concepts. Guides others, applying advanced principles and company practices. Leads moderate sized projects (or parts of larger projects) with strategic value. Operates autonomously with frequent senior leadership interaction.

Supervisor: No

TCP Career Step Differentiator: Performs complex data science work, build business models, and makes recommendations for improvements.

Education/Experience: Master's degree (MS/MA) required from an accredited University in a Quantitative field of study such as Data Science, Math, Statistics, Engineering or Physics. 3+ years of related experience. Certification is required in some areas.

Our Senior Data Scientist jobs earn between $139,000.00 - $233,500.00 USD Annual. Not to mention all the other amazing rewards that working at AT&T offers. Individual starting salary within this range may depend on geography, experience, expertise, and education/training.

Joining our team comes with amazing perks and benefits:

  • Medical/Dental/Vision coverage
  • 401(k) plan
  • Tuition reimbursement program
  • Paid Time Off and Holidays (based on date of hire, at least 23 days of vacation each year and 9 company-designated holidays)
  • Paid Parental Leave
  • Paid Caregiver Leave
  • Additional sick leave beyond what state and local law require may be available but is unprotected
  • Adoption Reimbursement
  • Disability Benefits (short term and long term)
  • Life and Accidental Death Insurance
  • Supplemental benefit programs: critical illness/accident hospital indemnity/group legal
  • Employee Assistance Programs (EAP)
  • Extensive employee wellness programs
  • Employee discounts up to 50% off on eligible AT&T mobility plans and accessories, AT&T internet (and fiber where available) and AT&T phone

Weekly Hours:

40

Time Type:

Regular

Location:

Atlanta, Georgia, Dallas, Texas

Salary Range:

$139,000.00 - $233,500.00

It is the policy of AT&T to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, AT&T will provide reasonable accommodations for qualified individuals with disabilities.AT&T is a fair chance employer and does not initiate a background check until an offer is made.

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