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Internship Deep Reinforcement Learning Jobs in Nevada

CreditOne

AVP, Artificial Intelligence

Las Vegas, NV · On-site

Supervised, unsupervised, reinforcement learning * Deep learning (CNNs, RNNs, Transformers) * Natural Language Processing (NLP) & LLMs * Generative AI (diffusion models, fine-tuning, RAG) * AI ...

Launch Potato

Lead Data Scientist, AdTech

Las Vegas, NV · Hybrid

$175K - $200K/yr

Hands-on experience across core technique areas: multi-armed bandit / reinforcement learning ... LLMs / deep learning applied to personalization or content * Familiarity with Looker TOTAL ...

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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.

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What job categories do people searching Internship Deep Reinforcement Learning jobs in Nevada look for? The top searched job categories for Internship Deep Reinforcement Learning jobs in Nevada are:
Internship Deep Reinforcement Learning jobs near you

Lead Artificial Intelligence Engineer

Credit One Bank

Las Vegas, NV • On-site

$97K - $128K/yr

Full-time

Re-posted 3 days ago

Job description

Job Summary:
Credit One Bank is a data-driven financial services company based in Las Vegas. They are seeking a Lead Artificial Intelligence Engineer to develop and produce AI and machine learning solutions that support banking and credit card businesses, focusing on building scalable, explainable, and compliant AI models for various applications.
Responsibilities:
• Develop, train, and optimize ML, deep learning, and Generative AI models.
• Implement data pipelines, feature engineering, and model inference services.
• Deploy and monitor models using enterprise MLOps practices.
• Support model explainability, bias analysis, and regulatory documentation.
• Collaborate with data engineers, risk, and compliance teams.
Qualifications:
Required:
• Develop, train, and optimize ML, deep learning, and Generative AI models.
• Implement data pipelines, feature engineering, and model inference services.
• Deploy and monitor models using enterprise MLOps practices.
• Support model explainability, bias analysis, and regulatory documentation.
• Collaborate with data engineers, risk, and compliance teams.
• Machine Learning & Modeling: Supervised, unsupervised, reinforcement learning.
• Deep learning (CNNs, RNNs, Transformers).
• Natural Language Processing (NLP) & LLMs.
• Generative AI (diffusion models, fine-tuning, RAG).
• AI Engineering & MLOps: Model training, deployment, monitoring, and retraining.
• Feature stores, vector databases, and model registries.
• CI/CD pipelines for ML (MLOps).
• GPU/accelerator compute architectures.
• Cloud & Infrastructure: Azure AI, Azure ML, AWS Sagemaker, or Google Vertex AI.
• Kubernetes, containerization, microservices.
• Data platforms (Databricks, Snowflake, Synapse).
• Responsible AI & Governance: Model explainability (SHAP, LIME).
• Fairness, bias detection, model risk controls.
• Privacy-preserving ML techniques (differential privacy, federated learning).
• Programming & Tooling: Python, PyTorch, TensorFlow, JAX.
• LangChain, semantic search, vector embeddings.
• Prompt engineering & LLM orchestration frameworks.
Preferred:
• Bachelor’s degree in Computer Science, Engineering, Data Science, or related field.
• 3–7 years of experience in AI/ML or data science.
• Experience working with large-scale financial or transactional data is preferred.
Company:
Credit One Bank is a financial services company that offers credit cards, credit score tracking, and fraud protection services. Founded in 1984, the company is headquartered in Las Vegas, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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