채용
Benefits & Perks
•E Verify
Required Skills
Python
PyTorch
Machine Learning
Multimodal Learning
Foundation Models
Reality Labs is building the future of connection through world-class AR/VR hardware and software. The XR Tech AIX (AI Experiences) team is developing cutting-edge real-time AI systems that power next-generation communication experiences. We are creating intelligent agents that seamlessly interface with fine-tuned foundation models to enable rich, real-time interactions in video calling and telepresence scenarios.We are seeking an exceptional Research Scientist Intern to join our team and contribute to the development of real-time multimodal AI systems. This role focuses on fine-tuning and optimizing large foundation models-particularly vision-language models-for real-time agent-based applications. You will work at the intersection of multimodal learning, real-time systems, and agentic AI.Our internships are twelve (12) to twenty-four (24) weeks long with a flexible summer start date.
Research Scientist Intern, Real-Time Multimodal AI (PhD) Responsibilities:
- Research and develop novel approaches for fine-tuning large multimodal foundation models (vision-language, audio-visual) for real-time applications
- Design and implement efficient inference pipelines for deploying fine-tuned models in real-time communication scenarios
- Explore agentic architectures that leverage fine-tuned models as tools within larger AI systems
- Collaborate with cross-functional teams to integrate models into prototype experiences
- Document and present research progress with the goal of publishing findings at top-tier ML/CV conferences
- Contribute to building working prototypes that demonstrate the capabilities of fine-tuned multimodal models
Minimum Qualifications:
- Currently has, or is in the process of obtaining, a PhD degree in Computer Science, Machine Learning, Electrical Engineering, or a related field
- 2+ years of research experience in one or more of the following areas: multimodal learning, vision-language models, large language models, or foundation model fine-tuning
- Hands-on experience fine-tuning large foundation models (e.g., LLaVA, InternVL, Qwen-VL, LLaMA, or similar)
- Strong programming skills in Python
- Experience with deep learning frameworks such as Py Torch
- Excellent communication skills and ability to work independently
- Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
Preferred Qualifications:
- Proven track record of achieving significant results as demonstrated by first-authored publications at leading conferences such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ICASSP, Interspeech, ACL, EMNLP, or similar
- Experience with speech-to-speech LLMs or audio-visual foundation models
- Familiarity with real-time communication systems (e.g., Live Kit, WebRTC) or low-latency inference optimization
- Experience with cloud infrastructure (AWS) and containerization (Docker)
- Experience with parameter-efficient fine-tuning techniques (LoRA, QLoRA, adapters, etc.)
- Experience with agentic AI systems, tool-use, or function-calling in LLMs
- Demonstrated software engineering experience via internships, work experience, or contributions to open source repositories (e.g., GitHub)
- Intent to return to degree program after completion of the internship
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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