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Internship Rlhf Jobs in California (NOW HIRING)

The internship will focus on building intelligent agents, generating high-quality trajectories ... Familiarity with training or adapting LLMs using SFT, RL, DPO/RLHF methods, or trajectory data.

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Internship Rlhf information

Is there a shortage of ML engineers?

The demand for ML engineers remains high across industries due to the growth of artificial intelligence and data-driven applications. Companies often seek candidates with skills in machine learning frameworks like TensorFlow or PyTorch, and a strong background in programming and statistics, leading to a competitive job market for qualified professionals.

What are Internship RLHF positions?

Internship RLHF positions refer to internships focused on Reinforcement Learning from Human Feedback (RLHF), a cutting-edge area in artificial intelligence research. Interns in RLHF roles typically work on projects that involve training AI models to align with human preferences using feedback data, often in natural language processing or robotics. These internships are usually offered by tech companies or research labs and provide hands-on experience in machine learning, data analysis, and experimental design. RLHF interns often collaborate with experienced researchers and engineers to advance AI systems' safety, reliability, and alignment with human values.

What jobs can I get with human computer interaction?

With a background in human-computer interaction (HCI), you can pursue roles such as user experience (UX) designer, usability analyst, interaction designer, or user researcher. These jobs involve designing and improving digital interfaces, often requiring skills in user research, prototyping, and familiarity with tools like Adobe XD or Figma.

Which 3 jobs will survive AI?

Jobs that require complex human interaction, creativity, and critical thinking, such as internships in research, healthcare, and skilled trades, are more likely to survive AI automation. Roles involving emotional intelligence, nuanced decision-making, and hands-on skills are less susceptible to automation. Developing expertise in these areas can improve job security in an internship setting.

What is the difference between Internship Rlhf vs Research Assistant?

AspectInternship RlhfResearch Assistant
Required CredentialsTypically enrolled students or recent graduatesUsually requires a relevant degree or ongoing education in the field
Work EnvironmentInternship programs, often in academic or research institutionsResearch labs, universities, or research-focused organizations
Employer & Industry UsageUsed by educational institutions and research organizations for trainingCommon in academia, government, and private research sectors
Search & Comparison IntentPeople comparing internship opportunities or entry-level research rolesIndividuals seeking research support or entry-level research positions

Internship Rlhf and Research Assistant roles both involve research activities, but internships are typically short-term training positions for students or recent graduates, while research assistants are more formal, often requiring relevant education and supporting ongoing research projects. Understanding these differences helps candidates choose the right opportunity based on their experience and career goals.

Is ML a high paying job?

Machine learning (ML) jobs, including roles like ML engineer or data scientist, tend to offer high salaries compared to many other tech positions due to the specialized skills required, such as programming, statistics, and experience with tools like TensorFlow or PyTorch. Entry-level positions may start lower, but experienced professionals often earn six-figure salaries, especially in industries like finance, tech, and healthcare.

What types of projects and tasks can I expect to work on during an RLHF internship?

As an RLHF (Reinforcement Learning from Human Feedback) intern, you can expect to engage in a variety of projects that combine machine learning, data annotation, and model evaluation. Typical tasks include curating and labeling datasets, training and fine-tuning machine learning models using human feedback, and conducting experiments to evaluate model performance. You may also collaborate closely with engineers and researchers, participate in team meetings, and contribute to documentation or research publications. This hands-on experience will help you develop both technical and collaborative skills essential for a career in AI research.

What are the key skills and qualifications needed to thrive as an RLHF (Reinforcement Learning from Human Feedback) Intern, and why are they important?

To thrive as an RLHF Intern, you need a solid background in machine learning, statistics, and programming (especially Python), usually supported by ongoing or completed studies in computer science or a related field. Experience with deep learning frameworks (such as TensorFlow or PyTorch), version control systems (like Git), and familiarity with reinforcement learning libraries are typically required. Strong problem-solving abilities, curiosity, and effective teamwork and communication skills help interns contribute meaningfully and learn quickly. These skills and qualities are crucial for successfully developing, evaluating, and improving RLHF models in a collaborative research environment.
What are the most commonly searched types of Rlhf jobs in California? The most popular types of Rlhf jobs in California are:
What cities in California are hiring for Internship Rlhf jobs? Cities in California with the most Internship Rlhf job openings:
Research Scientist 4 - Machine Learning and Inference Research, LLM Post-Training

Research Scientist 4 - Machine Learning and Inference Research, LLM Post-Training

Netflix

Los Angeles, CA

Other

Medical, Life, Retirement, PTO

Posted 6 days ago


Netflix rating

5.8

Company rating: 5.8 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

57th of 65 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 grows, we keep advancing innovations in personalization and discovery, experimentation and decision-making, understanding our members and our titles, and backend infrastructure. These developments constantly create new opportunities for research to drive meaningful impact.

By exploring the frontiers of AI/ML and intersecting fields, the Machine Learning and Inference Research team turns these opportunities into tangible benefits for our members and our business. The Machine Learning and Inference Research team is a dedicated research team building up Netflix's technical capabilities by tackling fundamental research questions tied to our most important challenges and partnering closely with teams across the business to translate research into impact at scale. As a member of the team, you will leverage your technical expertise to shape roadmaps, collaborate across functions, and bring new ideas from exploration to impact.

You will also engage actively with the broader research community by publishing at top venues, presenting at conferences, mentoring interns, and fostering academic collaborations. We are seeking an early-career researcher who can grow to define and execute a strong research agenda with both internal and external visibility, disseminate knowledge effectively and inspire others, collaborate with colleagues to deliver tangible impact, and help foster an open environment of innovation, intellectual rigor, and curiosity. What you bring Ph.D

in Computer Science or a related field with a specialization in post-training LLMs for downstream tasks, especially using RL (e.g., RLVR, RLHF, offline or online, policy- or value-based), and possibly also including reasoning, alignment, distillation/compression, tool use, memory, calibration, or related. A track record of top-tier publications demonstrating deep expertise in the specialization. Passion for collaboration and for building strong relationships to tackle big, cross-functional problems

Strong technical communication skills, with the ability to adapt to different audiences. Self-motivated with an ability to thrive and to lead with minimal oversight and process. Curiosity and judgment in identifying and framing ambiguous research and business problems, and connecting the two.

Eagerness to elevate the broader organization through sharing knowledge and guiding the adoption of new methods. 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 $300,000.00 - $537,000.00. 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

Hours and flexibility

Workplace

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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