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Research Engineer - Safety System and Foundations

Meta

Research Engineer - Safety System and Foundations

Meta

Menlo Park, CA

·

On-site

·

Full-time

·

1mo ago

Compensation

$183,040 - $183,040

Benefits & Perks

Parental leave

Professional development budget

Generous paid time off and holidays

Team events and activities

401(k) matching

Competitive salary and equity package

Parental Leave

Learning

Equity

Required Skills

Node.js

PostgreSQL

React

Meta is seeking Research Engineers to join the Safety System and Foundations team within Meta Superintelligence Labs, dedicated to advancing the safe development and deployment of Superintelligent AI. Our mission is to pioneer robust and foundational safety techniques that empower Meta's most ambitious AI capabilities, ensuring billions of users experience our products and services securely and responsibly.

Research Engineer

Safety System and Foundations Responsibilities:

  • Design, implement, and evaluate novel, systemic, and foundational safety techniques for large language models and multimodal AI systems
  • Create, curate, and analyze high-quality datasets for safety system and foundations
  • Fine-tune and evaluate LLMs to adhere to Meta's safety policies and evolving global standards
  • Build scalable infrastructure and tools for safety evaluation, monitoring, and rapid mitigation of emerging risks
  • Work closely with researchers, engineers, and cross-functional partners to integrate safety solutions into Meta's products and services
  • Lead complex technical projects end-to-end

Minimum Qualifications:

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • PhD in Computer Science, Machine Learning, or a relevant technical field
  • 3+ years of industry research experience in LLM/NLP, computer vision, or related AI/ML model training
  • Experience as a technical lead on a team and/or leading complex technical projects from end-to-end
  • Publications at peer-reviewed conferences (e.g. ICLR, NeurIPS, ICML, KDD, CVPR, ICCV, ACL)
  • Programming experience in Python and hands-on experience with frameworks such as Py Torch

Preferred Qualifications:

  • Hands-on experience applying state-of-the-art techniques to build robust AI system solutions for safety and policy adherence
  • Experience developing, fine-tuning, or evaluating LLMs across multiple languages and capabilities (text, image, voice, video, reasoning, etc)
  • Demonstrated experience to innovate in safety foundational research, including custom guideline enforcement, dynamic policy adaptation, and rapid hotfixing of model vulnerabilities
  • Experience designing, curating, and evaluating safety datasets, including adversarial and borderline prompt cases
  • Experience with distributed training of LLMs (hundreds/thousands of GPUs), scalable safety mitigations, and automation of safety tooling

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.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$88.46/hour to $257,000/year + bonus + equity + benefits
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 · Product Designer

1,471 reports

$273,432

total / year

Base

$180,290

Stock

$72,619

Bonus

$20,523

$186,170

$416,421

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