About the role#
This internship focuses on Recursive Self-Improvement (RSI) for video recommendation models. You will build AI agents that propose, run, evaluate, and learn from model improvements. The goal is to close the loop between machine learning experimentation and model quality. You will frame practical challenges in video recommendation as rigorous machine learning problems and develop an end-to-end prototype under the guidance of Research Scientists and Software Engineers.
What you'll do#
- Design and build an agent-driven RSI system for large-scale video recommendation models.
- Profile training data quality and implement interventions like filtering, sampling, and reweighting.
- Automate environment setups, training configurations, and offline evaluation pipelines.
- Create feedback loops to collect model quality signals and improve agent intervention strategies.
- Measure model quality against data-processing and training costs.
- Maintain versioned experiment records and automated checks.
- Collaborate with researchers and cross-functional partners to share plans and results.
- Publish research findings and contribute to work applicable to Meta product development.
What you'll need#
- Current enrollment in a Ph.D. program in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- Intent to return to your degree program after the internship.
- Experience with Python, C++, C, or Java.
- Proficiency with deep learning frameworks like PyTorch or TensorFlow.
- Understanding of machine learning and common deep learning architectures.
- Research experience in areas such as LLM-based agents, recursive self-improvement, AutoML, data-centric AI, reinforcement learning, or large-scale recommendation systems.
- Experience building reproducible ML pipelines on distributed training systems.
- A history of research achievements, including publications at major AI conferences.
- Demonstrated software development experience through internships, work, or open-source contributions.
- Ability to identify research opportunities and select appropriate ML methods for real-world applications.
- Valid work authorization in the United States at the time of hire and throughout the internship.
Location & details#
- Location: Menlo Park, California.
- Modality: On-site.
- Duration: 12 to 24 weeks with various start dates.
- Employment: Full-time internship.
- Compensation: $7,650 to $12,667 per month.
About Meta
Meta develops software and social media applications. It operates platforms such as Facebook, Messenger, Instagram, and WhatsApp. The company maintains headquarters in Menlo Park, California. Current work focuses on augmented and virtual reality alongside artificial intelligence and machine learning.
How to get in at Meta
Landing an internship at Meta requires a proactive approach to the application process. Intern Insider sends an instant alert the moment a role matching your target is published, allowing you to apply among the first. Early applicants often have their materials reviewed before the applicant pool grows significantly. You can use Intern Insider to surface the recruiters behind specific roles at Meta. Reaching out directly to these individuals to ask about the position or a referral often improves your response rates compared to applying into a queue.
