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Language Research Scientist

Meta

Language Research Scientist

Meta

Zurich, Switzerland

·

On-site

·

Full-time

·

2w ago

Benefits & Perks

Equity

Healthcare

401(k)

Equity

Healthcare

401k

Required Skills

Python

Reinforcement learning

Large language models

Distributed training

We are seeking a technically skilled GenAI scientist to join our team focused on Large Language Model (LLM) agents and model post-training, with a particular emphasis on reinforcement learning (RL). This role will be close to product applications and user impact, requiring full-stack knowledge.

Language Research Scientist Responsibilities:

  • Design, implement, and optimize LLM-based agents for a variety of applications, leveraging the latest advances in generative AI
  • Apply reinforcement learning algorithms to improve LLM performance, safety, and alignment
  • Integrate models and orchestrations in production
  • Collaborate with cross-functional teams (research, engineering, product) to deploy and evaluate LLM agents in real-world scenarios
  • Analyze and interpret experimental results, iterate on model architectures, and drive continuous improvement
  • Contribute to the broader AI/ML community at Meta through knowledge sharing, code reviews, and technical mentorship
  • Lead and contribute to research and development of post-training methods, including RLHF (Reinforcement Learning from Human Feedback), reward modeling, and other feedback-based approaches

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
  • Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience)
  • Good programming skills in Python and familiarity with large-scale distributed training
  • Familiarity to learn new programming languages quickly
  • Can design, implement, and evaluate RL algorithms in production or research settings
  • Problem-solving, communication, and collaboration skills

Preferred Qualifications:

  • Experience with RLHF, reward modeling, or other LLM post-training techniques
  • Experience working in cross-functional teams
  • Track record of publications or contributions to open-source projects in LLMs, RL, or related areas
  • Familiarity with safety, alignment, and evaluation challenges in generative AI

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