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Internship Deep Reinforcement Learning Jobs in Idaho

Micron

Staff Machine Learning Engineer

Boise, ID

Strong experience with ML frameworks (TensorFlow, PyTorch, scikit-learn) and core techniques including regression, classification, deep learning, reinforcement learning, and generative AI.

Varsity Tutors

BCABA Tutor

Idaho Falls, ID · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Deep knowledge of BCABA examination content covering basic behavior-analytic skills, philosophical ...

Varsity Tutors

BCABA Tutor

Rexburg, ID · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Deep knowledge of BCABA examination content covering basic behavior-analytic skills, philosophical ...

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Internship Deep Reinforcement Learning information

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 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 are the key skills and qualifications needed to thrive as an intern in deep reinforcement learning?

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 popular job titles related to Internship Deep Reinforcement Learning jobs in Idaho?

For Internship Deep Reinforcement Learning jobs in Idaho, the most frequently searched job titles are:

What job categories do people searching Internship Deep Reinforcement Learning jobs in Idaho look for?

The top searched job categories for Internship Deep Reinforcement Learning jobs in Idaho are:

What cities in Idaho are hiring for Internship Deep Reinforcement Learning jobs?

Cities in Idaho with the most Internship Deep Reinforcement Learning job openings:

Internship Deep Reinforcement Learning jobs near you
Infographic showing various Internship Deep Reinforcement Learning job openings in Idaho as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution.

Staff Machine Learning Engineer

Boise, ID • On-site

Micron Technology
Semiconductor and Electronic Component Manufacturing • 10K+ employees

8.6

Company rating: 8.6 out of 10

Based on 43 frontline employees who took The Breakroom Quiz

27th of 159 rated electronics manufacturers

People enjoy working here

Good employer

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Learn more about Micron Technologyexternal

Full-time

Re-posted 8 days ago

Job description

Job Summary:
Micron Technology is a world leader in innovating memory and storage solutions. They are seeking a Staff Machine Learning Engineer to deliver industry-winning machine learning solutions for their manufacturing processes, collaborating with various teams to build and deploy scalable AI/ML solutions.
Responsibilities:
• Analyze large datasets to uncover patterns, trends, and insights that inform and improve machine learning models.
• Design, build, and continuously refine ML models to address business challenges and enhance product capabilities.
• Stay ahead of advancements in AI/ML and integrate emerging techniques into the MLOps lifecycle.
• Build and maintain robust, scalable data pipelines and infrastructure to support model training and deployment.
• Collaborate on data preprocessing and feature engineering to improve input data quality and model performance.
• Design and optimize data architectures across cloud platforms (Snowflake, GCP, Azure) for AI/ML use cases.
• Develop custom applications and implement CI/CD pipelines to support efficient ML solution deployment.
• Deploy, evaluate, and monitor models in production, balancing performance with cost efficiency and enabling continuous improvement.
• Partner with Product and Engineering teams to define and execute Generative AI integration strategies and roadmaps.
• Communicate insights and collaborate multi-functionally, translating complex analytics into actionable recommendations for diverse collaborators.
Qualifications:
Required:
• Master's degree in Computer Science, Machine Learning, Data Science, Statistics, or a field closely related to AI and Machine Learning with 3+ years building end-to-end ML systems on cloud platforms, automating model training, testing, and deployment.
• Strong experience with ML frameworks (TensorFlow, PyTorch, scikit-learn) and core techniques including regression, classification, deep learning, reinforcement learning, and generative AI.
• Proficient in Python or Java, with experience developing APIs and event-driven pipelines using Kafka, Pub/Sub, or similar messaging systems.
• Skilled in scalable data engineering, including ETL/ELT pipelines (Kubeflow, Airflow, Dataflow), SQL, and data architecture design.
• Hands-on experience with cloud and DevOps tools (GCP, AWS, Azure, Docker, Kubernetes), combined with strong analytical, communication, and collaboration skills.
Preferred:
• Strong foundation in machine learning and deep learning, with solid grounding in probability and statistics.
• Proven ability to productionize data science prototypes into scalable, real-world solutions.
• Hands-on experience building Generative AI solutions and intelligent agents (LangChain/LangGraph, CrewAI, DsPy, Semantic Kernel, ADK).
• Expertise in semantic search and retrieval systems, including RAG, GraphRAG, NLP, prompt engineering, and LLM fine-tuning/evaluation.
• Experience with end-to-end data and engineering workflows: ETL pipelines, big data processing, databases (BigQuery, Snowflake, MSSQL, PostgreSQL), and CI/CD tools (Git, Docker, Kubernetes, Jenkins).
Company:
Micron Technology is a semiconductor company that produces DRAM, SDRAM, flash memory, SSD and CMOS image sensing chips. Founded in 1978, the company is headquartered in Boise, USA, with a team of 10001+ employees. The company is currently Late Stage.

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