Jobs
Benefits & Perks
•401(k) matching
•Parental leave
•Comprehensive health, dental, and vision insurance
•Generous paid time off and holidays
•Competitive salary and equity package
•Professional development budget
•Parental Leave
•Healthcare
•Equity
•Learning
Required Skills
PostgreSQL
Python
JavaScript
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.
Research Scientist Intern, RL and Agents Team, PhD (Paris) 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 with Python, C++, C, Java or other related languages.
- Experience building systems based on machine learning and/or deep learning methods.
Minimum Qualifications:
- Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Artificial Intelligence, Generative AI, or a relevant technical field
- Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment
- Experience with Python, C++, C, Java or other related languages
- Experience building systems based on machine learning and/or deep learning methods
Preferred Qualifications:
- Intent to return to the 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 first-authored publications at leading workshops or conferences such as NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, ICCV, ECCV, or similar
- Experience working and communicating cross functionally in a team environment
- Experience in advancing agentic AI techniques, including core contributions to open source libraries and frameworks in agentic LLMs or RL environments
- Publications or experience in agentic AI, LLMs, reinforcement learning, reasoning/coding, optimization, computer science, statistics, applied mathematics, or data science
- Experience solving analytical problems using quantitative approaches
- Experience setting up ML experiments and analyzing their results
- Experience manipulating and analyzing complex, large scale, high-dimensionality data from varying sources
- Experience in utilizing theoretical and empirical research to solve problems
- Experience with deep learning frameworks
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
PublicA 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
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