AI Research Scientist, MRS Knowledge

Meta•Menlo Park, CA

6h•$154,000 - $217,000

About The Position

The MRS AI Knowledge team works on content understanding, user understanding, retrieval, and ranking. The team advances recommendation systems using AI, including large language models and generative AI, to improve user experiences across Facebook, Instagram, Threads, and other products. The AI Research Scientist designs and conducts original research in core machine learning, develops reusable research code and scalable experimental pipelines, and helps define research directions and milestones. The role analyzes experiments, contributes to publications and open-source efforts, and collaborates with product and engineering teams to apply research findings to Meta's AI systems. It also establishes evaluation frameworks and benchmarks, mentors team members, coordinates cross-functional initiatives, and identifies opportunities to improve research programs and methods.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
6+ years of experience in machine learning research, including hands-on work with deep learning, optimization, generative models, or related core machine learning areas.
Experience developing and publishing novel machine learning approaches at peer-reviewed venues such as NeurIPS, ICML, ICLR, or CVPR, or equivalent.
Experience designing and running large-scale machine learning experiments, including model training, evaluation, and iterative refinement using frameworks such as PyTorch or TensorFlow.
Experience communicating research findings and technical trade-offs in writing to research and non-research audiences, such as through papers, technical reports, or design documents.
Experience collaborating across research and engineering teams to drive projects from ideation through production impact.

Nice To Haves

Experience mentoring researchers or engineers and contributing to team research culture, evaluation standards, or shared tooling.
Experience applying core machine learning research to large-scale production systems, including work with high-dimensional, large-volume datasets and distributed training infrastructure.
PhD in Machine Learning, Computer Science, Statistics, or a closely related field, with a dissertation focused on a core machine learning topic.
Track record of high-impact publications or open-source contributions widely adopted or cited within the machine learning research community.

Responsibilities

Design and execute original research in core machine learning, including deep learning architectures, optimization methods, representation learning, or generative modeling.
Develop and maintain high-quality, reusable research code and experimental pipelines for reproducible and scalable machine learning research.
Identify and define long-term research directions and near-term milestones aligned with team and organizational goals.
Analyze experimental results using rigorous statistical and empirical methods to draw actionable conclusions and inform future research.
Contribute to publications at top-tier machine learning venues and support open-sourcing efforts that advance the research community.
Collaborate with product and engineering teams to translate fundamental research findings into practical improvements in Meta's AI systems.
Establish and improve telemetry, evaluation frameworks, and benchmarks to measure research progress and model quality.
Provide technical guidance and mentorship to engineers and researchers through design reviews, research critiques, and knowledge-sharing sessions.
Drive cross-functional research initiatives with collaborators across AI infrastructure, product, and applied science teams.
Identify gaps in research programs or methodologies and propose improvements to strengthen the team's research output.