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Research Scientist Intern, RL and Agents Team (MSc)

Meta

Research Scientist Intern, RL and Agents Team (MSc)

Meta

Paris, France

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

401(k) matching

Competitive salary and equity package

Comprehensive health, dental, and vision insurance

Parental leave

Equity

Healthcare

Parental Leave

Required Skills

JavaScript

React

Node.js

Meta was built to help people connect and share, and over the last decade our tools have played a critical part in changing how people around the world communicate with one another. With over a billion people using the service and more than fifty offices around the globe, a career at Meta offers countless ways to make an impact in a fast growing organization.

Meta is seeking Research Interns to join our Meta Superintelligence Lab in one of the post-training modeling team, with a focus on Agentic AI and Products. We are committed to advancing the field of artificial intelligence by making fundamental advances in technologies that help interact with and understand our world. We are seeking individuals passionate about agentic AI, including but not limited to LLM agentic tool use, personalized AI agents, LLM agentic post-training, LLM reasoning/coding, and related areas. Our interns have an opportunity to make core algorithmic advances, prototype agentic features for Meta products, and apply their ideas at an unprecedented scale.

Our internships are twelve (12) to sixteen (16), or twenty-four (24) weeks long and we have various start dates throughout the year. It could be extended to a PhD CIFRE.

Research Scientist Intern, RL and Agents Team (MSc) Responsibilities:

  • Develop novel state-of-the-art agentic AI algorithms and corresponding systems, leveraging machine learning and reinforcement learning techniques.
  • Conduct research on agentic LLMs, agentic RL environments, LLM post-training, and related topics.
  • Analyze and improve the efficiency, scalability, and stability of agentic AI algorithms and deployed systems.
  • Advance the science and technology of intelligent, agentic machines capable of reasoning, tool use, and personalized interactions.
  • Collaborate with researchers and cross-functional partners, including communicating research plans, progress, and results.
  • Disseminate research results through publications, presentations, and open source contributions.
  • When applicable, contribute to research that can be applied to Meta product development.
  • Experience building systems based on machine learning and/or deep learning methods.

Minimum Qualifications:

  • Currently has or is in the process of obtaining a Masters degree in the field of Natural Language Processing, Machine Learning, Artificial Intelligence, or similar or relevant technical field
  • Research and/or work experience in Natural Language Processing
  • Research and/or work experience in Machine Learning or Deep Learning
  • Experience in Python, C++, or other related languages
  • Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment

Preferred Qualifications:

  • Intent to return to degree program after the completion of the internship/co-op
  • Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as publications at leading workshops or conferences (ICML, ICLR, NeurIPS, ACL, EMNLP, POPL, ACM)
  • Experience advancing AI techniques, including contributions to open source libraries and frameworks
  • Experience advancing AI techniques in NLP, Computer Vision, Speech, and/or Machine Learning
  • Experience manipulating and analyzing complex, large scale, high-dimensionality data from varying sources
  • Experience in utilizing theoretical and empirical research to solve problems
  • Experience working and communicating cross functionally in a team environment

About Meta:

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and Whats App further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today-beyond the constraints of screens, the limits of distance, and even the rules of physics.

Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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About Meta

Meta

Meta

Public

A social technology company that enables people to connect, find communities, and grow businesses.

10,001+

Employees

Menlo Park

Headquarters

$800B

Valuation

Reviews

3.4

26 reviews

Work Life Balance

2.3

Compensation

4.2

Culture

2.8

Career

3.1

Management

2.1

45%

Recommend to a Friend

Pros

Excellent compensation and benefits

Smart and talented colleagues

Fast-paced and challenging work environment

Cons

Frequent layoffs and job insecurity

Poor leadership and management accountability

High stress and competitive work environment

Salary Ranges

40,175 data points

Mid/L4

Mid/L4 · Data Scientist

3,113 reports

$284,667

total / year

Base

$179,458

Stock

$79,981

Bonus

$25,228

$193,897

$434,902

Interview Experience

6 interviews

Difficulty

4.2

/ 5

Duration

21-35 weeks

Offer Rate

17%

Experience

Positive 17%

Neutral 17%

Negative 66%

Interview Process

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Coding Interviews

6

System Design Interview

7

Behavioral Interview

8

Final Loop/Hiring Manager Round

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Live Coding