채용
Benefits & Perks
•Learning and development stipend
•Wellness benefits
•Health, dental, and vision coverage
•Annual team offsites
Required Skills
SQL
PyTorch
Airflow
We are the Monetization Ranking AI Research organization, dedicated to delivering personalized ads that maximize both user utility and advertiser value. We focus on advancing AI and ML technologies for all aspects of Monetization, including ranking, retrieval, model architecture, and optimization. By consistently integrating cutting-edge AI/ML advancements, we help Meta's products achieve long-term goals and have contributed tens of billions in revenue. With our growing impact, we're seeking AI Research Scientists to join our team and drive SOTA research across the Monetization organization.
AI Research Scientist, Core
ML - Monetization AI Responsibilities:
- Develop and implement large-scale model architectures, leveraging model scaling and transfer learning techniques
- Prioritize training scalability and signal scaling to optimize model performance, efficiency, and reliability
- Develop and apply Next Gen sequence learning techniques to drive advancements in natural language processing and understanding
- Design and implement generative modeling solutions for data augmentation
- Research and develop graph-aware large language models
- Develop and deploy AutoML pipelines
- Apply Reinforcement Learning (RL) techniques, including long-term value optimization, RLHF, and RL4Reason
- Use causal learning to identify and understand the cause and effect of relationships across data
- Collaborate with cross-functional teams to design and optimize ML systems, leveraging expertise in hardware-software co-design, including quantization, compression, and resource-efficient AI, to drive performance improvements and efficiency gains
- Develop and implement innovative solutions for data-related challenges, utilizing knowledge of semi/self-supervised learning, generative techniques, sampling, debiasing, domain adaptation, continual learning, data augmentation, cold-start, content understanding, and large language models
Minimum Qualifications:
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- Has obtained a PhD in Computer Science, Computer Engineering, Artificial Intelligence, Machine Learning, or relevant technical field
- Experience holding an industry, faculty, or government researcher position
- Research experience in natural language processing, large language modeling, deep learning, reinforcement learning, recommendations, ranking, search, or related areas
- Publications in machine learning, artificial intelligence, or related field
- Programming experience in Python and hands-on experience with frameworks such as Py Torch
- Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment
Preferred Qualifications:
- Experience taking ideas from research to production.
- First author publications at peer-reviewed AI conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, and ACL).
- Experience solving complex problems and comparing alternative solutions, tradeoffs, and different perspectives to determine a path forward.
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.
$154,000/year 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.
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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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