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Fundamental AI Researcher - FAIR

Meta

Fundamental AI Researcher - FAIR

Meta

New York, NY

·

On-site

·

Full-time

·

1mo ago

Compensation

$153,920 - $153,920

Benefits & Perks

Parental leave program

Top Tier compensation with equity

Annual team offsites

Health, dental, and vision coverage

Required Skills

TensorFlow

SQL

Apache Spark

Meta is seeking a researcher to join the Fundamental AI Research (FAIR) team, a research organization focused on advancing the state-of-the-art in AI. In this role, you'll work with world-class researchers at FAIR on fundamental and exploratory research. The team focuses on research in developing learning algorithms with enhanced reasoning, memory and alignment methods. Our current projects span improved learning objectives, self-supervised learning objectives, higher-level reasoning, and new memory techniques. Our organization is motivated by producing new science to understand intelligence and technology towards achieving advanced machine intelligence.

Fundamental AI Researcher

FAIR Responsibilities:

  • Perform research to advance the science and technology of intelligent machines, particularly on topics around reasoning, alignment and memory
  • Perform research that enables learning the semantics of data (images, video, text, audio, and other modalities)
  • Work towards long-term research goals, while identifying immediate milestones
  • Influence progress of relevant research communities by producing publications
  • Open source high quality code and produce reproducible research

Minimum Qualifications:

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • A PhD in AI, computer science, data science, or related technical fields
  • 2+ years of industry or equivalent Post Doctoral experience in relevant research areas, such as: machine learning, optimization, computer vision, natural language processing
  • First-authored publications at peer-reviewed conferences, such as ACL, EMNLP, NeurIPS, ICML, ICLR and other similar venues
  • Experience holding an industry, postdoctoral, faculty, or government researcher position
  • Research background in machine learning, artificial intelligence, computational statistics, applied mathematics, or related areas
  • Research publications reflecting experience in theoretical or empirical research
  • Experience in developing and debugging in Python or similar programming languages
  • Experience in analyzing and collecting data from various sources

Preferred Qualifications:

  • Research and engineering experience demonstrated via publications, grants, fellowships, patents, internships, work experience, open source code, and / or coding competitions
  • Experience in developing optimization algorithms and theory, distributed training of large-scale machine learning models, and comparing alternative solutions, trade-offs, and different perspectives
  • Experience collaborating in a team environment on research projects

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.

$74.04/hour to $217,000/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.

Contact & Location

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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