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Remote Reinforcement Learning Jobs in California

Senior Director, AI

Bodega Bay, CA · On-site +1

$257K - $402K/yr

Strong expertise in core AI domains, including computer vision, reinforcement learning, and large ... This is a fully remote role with the option to work hybrid if a commutable distance from our Salem ...

Based in Palo Alto, CA (Hybrid) / Remote (U.S.) * Deep experience in: * Frontend: React / Next.js ... Reinforcement learning training platforms * Evaluation and experimentation frameworks * Developer ...

Quartz ranked us the #1 best company for remote workers Responsibilities Workato's AI Research Lab ... reinforcement learning techniques, and CUDA. * Deep expertise across structured and unstructured ...

Quartz ranked us the #1 best company for remote workers Responsibilities Workato's AI Research Lab ... reinforcement learning techniques, and CUDA. * Deep expertise across structured and unstructured ...

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Remote Reinforcement Learning information

What is a Remote Reinforcement Learning job?

A Remote Reinforcement Learning job involves developing and applying reinforcement learning algorithms while working from a location outside of a traditional office environment. Professionals in this field focus on creating systems where agents learn optimal behaviors through trial and error, often using feedback from their environment. These jobs typically require expertise in machine learning, programming, and mathematics, and are commonly found in industries like robotics, gaming, and autonomous systems. Working remotely allows researchers and engineers to collaborate with global teams using digital tools and platforms.

What are the key skills and qualifications needed to thrive as a Remote Reinforcement Learning Engineer, and why are they important?

To thrive as a Remote Reinforcement Learning Engineer, you need a strong background in machine learning, statistics, and programming (especially Python), often supported by an advanced degree in computer science or a related field. Familiarity with frameworks such as TensorFlow, PyTorch, and RL-specific libraries like OpenAI Gym, along with experience using cloud computing platforms, is typically required. Excellent problem-solving skills, self-motivation, and effective remote communication help individuals excel in distributed teams. These skills ensure the successful design, implementation, and deployment of reinforcement learning solutions while collaborating efficiently in a remote work environment.

What is the difference between Remote Reinforcement Learning vs Remote Machine Learning Engineer?

AspectRemote Reinforcement Learning
Required CredentialsMaster's or PhD in Computer Science, AI, or related fields; knowledge of RL algorithms
Work EnvironmentResearch-focused, experimental, often involves simulation and algorithm development
Employer & Industry UsageTech companies, research labs, AI startups focusing on autonomous systems
Common Search & Comparison IntentUnderstanding specialized AI roles, research focus, and technical skills

Remote Reinforcement Learning specialists focus on developing algorithms that enable machines to learn through trial and error in simulated or real environments. In contrast, Remote Machine Learning Engineers typically work on deploying and optimizing various machine learning models across applications. While both roles require strong programming skills and knowledge of AI, reinforcement learning emphasizes decision-making processes, whereas machine learning engineering covers a broader range of models and deployment strategies.

What are common challenges faced when working remotely in a Reinforcement Learning role and how can they be addressed?

Working remotely in a Reinforcement Learning role often involves overcoming communication barriers with cross-functional teams, managing large-scale experiments without on-site resources, and staying updated with rapidly evolving research. To address these challenges, it's important to establish regular check-ins with colleagues, utilize cloud-based platforms for experiment management, and participate in virtual seminars or journal clubs. Developing strong self-motivation and time management skills is also crucial to maintain productivity in a remote environment.
What are the most commonly searched types of Reinforcement Learning jobs in California? The most popular types of Reinforcement Learning jobs in California are:
What job categories do people searching Remote Reinforcement Learning jobs in California look for? The top searched job categories for Remote Reinforcement Learning jobs in California are:
What cities in California are hiring for Remote Reinforcement Learning jobs? Cities in California with the most Remote Reinforcement Learning job openings:
AI/ML Scientist Intern, AIMS AI Foundations (PhD) - Fall 2026

AI/ML Scientist Intern, AIMS AI Foundations (PhD) - Fall 2026

Netflix

Los Gatos, CA • On-site, Remote

Full-time

Medical, Life, Retirement, PTO

Posted 26 days ago


Netflix rating

5.8

Company rating: 5.8 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

58th of 67 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.

Netflix is one of the world's leading entertainment services, with over 300 million paid memberships in over 190 countries enjoying TV series, films, and games across a wide variety of genres and languages. Members can play, pause, and resume watching as much as they want, anytime, anywhere, and can change their plans at any time.

The AIMS AI Foundations team sits within the AI for Member Systems (AIMS) organization and focuses on the research and engineering foundations that underpin next-generation member experiences. Our work spans agentic AI systems, LLM evaluation frameworks, multimodal modeling and training data curation. We work at the intersection of applied research and product impact, translating novel ideas into measurable improvements for Netflix members worldwide.

We are seeking a PhD intern to join us for a Fall 2026 engagement (targeting a September 2026 start, with flexibility). This is a hands-on applied research role: you will be expected to design and run experiments, build prototypes, and contribute meaningfully to ongoing team projects in one or more of our core domain areas.

Domain Areas

Interns will be matched to projects within one or more of the following focus areas:

  • Agentic AI - Developing and evaluating systems that reason, plan, and act autonomously, including tool use, retrieval-augmented reasoning, memory and goal management, and feedback-driven learning.

  • LLM Evaluations - Designing rigorous evaluation frameworks, benchmarks, and quality metrics to assess language model behavior, reliability, and alignment.

  • Multimodal Data - Building models and pipelines that integrate text, image, video, audio, and other data modalities; experience with large vision-language models and modality fusion.

  • LLM Training Data Curation - Researching and implementing methods for selecting, filtering, and improving training data quality to enhance model performance.

QualificationsMust Have
  • Currently enrolled PhD student in Computer Science, Machine Learning, Artificial Intelligence, Computer Engineering, Mathematics, Statistics, Data Science, Cognitive Science, or a related field

  • Able to work 40 hours per week during the fall/winter

  • Proficiency in Python

  • Strong foundation in machine learning, deep learning, and algorithms/statistics

  • Experience with one or more major ML frameworks: PyTorch, TensorFlow, or JAX

  • Ability to design, run, and interpret ML experiments in an applied research setting

  • Ability to translate research ideas into practical prototypes and evaluations

  • Strong oral and written communication skills for presenting technical work clearly

Nice to Have
  • Coursework or research experience in advanced NLP, advanced ML systems, or reinforcement learning

  • Familiarity with HuggingFace, Transformers, Pandas, NumPy, and scikit-learn

  • Publications in top venues such as NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL, AAAI, CIKM, WWW, UAI, CVPR, or related

  • Experience with agentic systems, multimodal modeling, or applied LLM workflows

  • Exposure to evaluation design, benchmarking, and model quality tradeoffs

  • Familiarity with distributed computing environments such as Spark or Presto

  • Comfortable with software engineering best practices (version control, testing, code review)

About the Internship

At Netflix, we offer a personalized experience for interns. Our aim is to provide an experience that mirrors what it is truly like to work here. Interns are fully embedded within their team, own meaningful projects, and operate with the same autonomy as full-time employees.

  • Internship duration: minimum 12 weeks, targeting a September 2026 start date

  • Location: Los Gatos, CA headquarters or remote; flexible depending on team

  • This program is intended for students who will be returning to school for at least one semester/quarter following the internship

For Your Application to Be Considered Complete
  • Submit your application on our Netflix Careers site

  • Complete the Airtable supplemental form sent after initial application submission - applications are not considered complete without it

  • Include a resume or CV with complete contact information, relevant coursework, and publications (if applicable)

  • Include a short statement describing your research experience and interests, and optionally their relevance to the AIMS AI Foundations team's focus areas

  • Applications are reviewed on a rolling basis. For inspiration, visit the Netflix Research site.

At Netflix, we carefully consider a wide range of compensation factors to determine the Intern top of market. We rely on market indicators to determine compensation and consider your specific job, skills, and experience to get it right. These considerations can cause your compensation to vary and will also be dependent on your location. The overall market range for Netflix Internships is typically $40/hour - $85/hour.

This market range is based on total compensation (vs. only base salary), which is in line with our compensation philosophy. Netflix is a unique culture and environment. Learn more here.

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.


What Netflix employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


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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