About the role#
Meta is looking for AI Research interns to join the Video Recommendations team. You will work on the infrastructure that powers video discovery across Reels, long videos, and Live streams. The role involves researching and building AI agents to analyze, optimize, and improve recommendation infrastructure. You will work at the intersection of machine learning, systems, and GPU computing to turn research into measurable gains in training and inference performance. Internships last between 12 and 24 weeks with various start dates available.
What you'll do#
- Research and develop AI agents that optimize training and inference for video recommendation models, including distributed execution, data pipelines, and model compilation.
- Investigate recursive self-improvement for infrastructure by using profiling traces and validated experiment results to improve performance.
- Build GPU kernel agents that generate and tune CUDA or Triton kernels, explore memory access and kernel fusion, and verify numerical correctness.
- Develop agentic trace analyzers to correlate CPU/GPU timelines and runtime telemetry to diagnose bottlenecks.
- Build agentic profilers that select profiling tools, collect targeted measurements, and recommend optimizations for compute, memory, communication, and scheduling.
- Design reproducible benchmarks to measure training throughput, inference latency, GPU utilization, memory use, and cost.
- Collaborate with Research Scientists and Software Engineers to scope experiments and build research prototypes.
- Communicate research plans and results through technical reports, tools, and publications.
What you'll need#
- Current enrollment in a Ph.D. program for Computer Science, Computer Engineering, Artificial Intelligence, Machine Learning, or a related field.
- Programming experience in Python, C++, or a related language.
- Experience with deep learning frameworks like PyTorch or TensorFlow.
- Familiarity with machine learning and the fundamentals of training or inference systems.
- Research or project experience in machine learning systems, performance optimization, GPU computing, distributed systems, or AI agents.
- Work authorization in the country of employment at the time of hire.
- Intent to return to your degree program after the internship.
- Preferred experience includes developing LLM agents, reinforcement learning, GPU kernel optimization, profiling workloads using tools like NVIDIA Nsight, and working with large-scale video recommendation infrastructure.
- A record of research achievements such as publications in venues like MLSys, NeurIPS, or OSDI is a plus.
Location & details#
- Location: Menlo Park, California, United States.
- Modality: On-site.
- 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.
