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Internship Deep Reinforcement Learning Jobs in Oregon

OR

$466K - $750K/yr

Reinforcement Learning-based Data Pipeline Optimization for Deep Recommendation Models Evidence Personalization Page Simulation for Better Offline Metrics at Netflix RecSysOps As a software engineer ...

... of-Thought, alongside reinforcement fine-tuning (RFT) to ensure agents provide accurate ... Deep experience with agentic frameworks, such as LangChain or Claude Agent SDK, retrieval-augmented ...

$32 - $40/hr

Overview This internship centers on researching and developing advanced healthcare informatics ... Hands-on experience with working with Machine Learning and Deep Learning models. Experience with ...

BCABA Tutor

OR · 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 ...

BCABA Tutor

Portland, OR · 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 ...

BCABA Tutor

Eugene, OR · 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 ...

$32 - $40/hr

We are currently looking for interns who can start in the Summer or Fall of 2026. Responsibilities ... Hands-on experience with working with Machine Learning and Deep Learning models. Experience with ...

$32 - $40/hr

We are currently looking for interns who can start in the Summer or Fall of 2026. Responsibilities ... Hands-on experience with working with Machine Learning and Deep Learning models. Experience with ...

$32 - $40/hr

Overview This internship centers on researching and developing advanced healthcare informatics ... Hands-on experience with working with Machine Learning and Deep Learning models. Experience with ...

Showing results 21-40

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?

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 Oregon? For Internship Deep Reinforcement Learning jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Internship Deep Reinforcement Learning jobs in Oregon look for? The top searched job categories for Internship Deep Reinforcement Learning jobs in Oregon are:
What cities in Oregon are hiring for Internship Deep Reinforcement Learning jobs? Cities in Oregon with the most Internship Deep Reinforcement Learning job openings:

Software Engineer 4/5- AI for Member Systems

Netflix

OR

$466K - $750K/yr

Full-time

Medical, Life, Retirement, PTO

Re-posted 19 days ago


Netflix rating

5.8

Company rating: 5.8 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

70th of 76 rated media


Job description

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology.

Come be a part of what's next. As Netflix continues to grow, so do the opportunities to enhance our personalization systems and algorithms. We're looking for a passionate and talented Software Engineer for Machine Learning to join our Al for Member Systems team.

In this role, you will apply your expertise in software engineering to design, develop, and scale solutions for the machine learning algorithms that power the Netflix experience. You will work closely with our machine learning researchers, product managers, and other engineers to come up with new systems, improve existing ones, and enable offline experiments and A/B tests. For more details about software engineering for personalization at Netflix, see these links: Consolidating ML models InTune: Reinforcement Learning-based Data Pipeline Optimization for Deep Recommendation Models Evidence Personalization Page Simulation for Better Offline Metrics at Netflix RecSysOps As a software engineer in the team, you will contribute to the next generation of algorithms used to generate the Netflix experience by driving the vision, requirements, design, implementation, testing, and ownership of software components essential for our algorithmic innovation.

You will collaborate with our applied researchers and data scientists to implement scalable, flexible, production-ready solutions for our algorithms. You will also guide the team towards better software engineering practices and systems by identifying areas for improvement and mentorship. You will collaborate with other engineers to create solutions that are used beyond our team.

To excel in this role, you should have a robust software engineering background, a keen sense of software engineering principles and design, a proven experience with large-scale applications involving machine learning, a love of learning, possess strong communication skills, and the ability to work well in large cross-functional teams. What we are looking for: A degree in Computer Science or a related field 4+ years of full time software engineering experience with a bachelor's degree; or 2+ years of experience with a graduate degree Excellent software design and development skills in Python along with Scala, Java, C++, or C# Solid understanding of various software engineering best practices and their appropriate application Experience building web-scale parallel and distributed computing systems Experience with large-scale data frameworks such as Spark or Flink Excellent collaboration skills Broad understanding of core machine learning concepts and their application in large-scale, real-world machine-learning systems Preferred, but not required: Experience building or enhancing personalization systems, machine learning platforms, search engines, or similar large-scale machine learning applications. Experience building machine learning models or LLMs Experience scaling and optimizing the training and serving of machine learning models Experience with machine learning libraries TensorFlow, PyTorch, JAX or Keras Experience with cloud computing platforms like AWS Background in math, statistics, or numerical computation Significant contributions to open-source projects Generally, our compensation structure consists solely of an annual salary; we do not have bonuses.

You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $466,000.00 - $750,000.00

This compensation range will vary based on location. Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs.

Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here.

Netflix is a unique culture and environment. Learn more here. Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates.

If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner. We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully.

We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service. Job is open for no less than 7 days and will be removed when the position is filled.


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About Netflix

Sourced by ZipRecruiter

Netflix is the world's leading streaming entertainment service with 222 million paid memberships in over 190 countries enjoying TV series, documentaries, feature films and mobile games across a wide variety of genres and languages. Members can watch as much as they want, anytime, anywhere, on any Internet-connected screen. Members can play, pause and resume watching, all without commercials or commitments.

Industry

Arts, entertainment, and recreation

Company size

5,001 - 10,000 Employees

Headquarters location

Los Gatos, CA, US

Year founded

1997