Jobs
Benefits & Perks
•Competitive salary and equity package
•Comprehensive health, dental, and vision insurance
•Generous paid time off and holidays
•Team events and activities
•Equity
•Healthcare
Required Skills
JavaScript
Python
Node.js
Meta is seeking Research Interns to join the FAIR Chemistry team. The Chemistry team develops AI-based methods to model the world at the atomic level. Chemistry and materials science applications include energy sustainability, drug discovery and new materials for display technologies.
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, FAIR Chemistry Responsibilities:
- Advancing the state-of-the-art in AI for generative atomic world models.
- Developing datasets to train and test AI models for Chemistry.
- Developing, training, and scaling AI models for Chemistry in Py Torch.
- Running large-scale chemistry simulations.
- Developing processes to feedback experimental results into chemistry models.
- Efficiency optimization of classic and ML based chemistry software.
- Writing research papers and associated open source data and code releases.
Minimum Qualifications:
- Currently has or is in the process of obtaining a Ph.D. degree in Machine Learning, Chemistry, Chemical Engineering, Physics, Artificial Intelligence, or relevant technical field
- Experience applying artificial intelligence to a scientific domain such as computational photonics, computational design, computational chemistry, etc
- Experience devising data-driven models and real-system experiments and design implementation for AI design and optimization
- Experience with scalable machine learning systems, resource-efficient AI data and algorithm scaling, or neural network architectures
- Experience with Python, C++, C, Julia, or other related language
- Experience with deep learning frameworks such as Pytorch, Jax, or Tensorflow
- Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment
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, CVPR, ICCV, ICLR, or similar
- Experience solving analytical problems using quantitative approaches
- Ability to manipulate and analyze complex, large scale, high-dimensionality data from varying sources
- Experience in utilizing theoretical and empirical research to solve problems
- Experience doing optimization based on machine learning and/or deep learning methods
- Demonstrated software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
- competitions, or widely used contributions in open source repositories (e.g. GitHub). 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.
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.
$7,650/month to $12,134/month + 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
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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