Description

Meta is seeking a Research Scientist to join its AI research organization, focused on advancing core machine learning methods that power Meta's products and platforms at scale. In this role, you will conduct applied and foundational ML research with an emphasis on Reinforcement Learning and Large Language Models (LLMs), contributing to systems that serve billions of users. You will collaborate with a multidisciplinary team of researchers and engineers to translate research insights into measurable product impact.

Research Scientist, Machine Learning Responsibilities:

• Design and execute machine learning research experiments, including model architecture design, training recipe development, and rigorous evaluation across benchmarks and production metrics
• Develop and optimize ML models and algorithms targeting core research problems such as representation learning, generative modeling, or large-scale optimization
• Implement clean, reusable, and well-tested research code using modern ML frameworks such as PyTorch, contributing to shared research infrastructure
• Analyze experimental results to form data-driven conclusions, identify failure modes, and iterate on hypotheses in collaboration with research and engineering partners
• Contribute to the preparation and submission of research findings to peer-reviewed venues such as NeurIPS, ICML, ICLR, or CVPR
• Partner with cross-functional teams including product engineering, data science, and infrastructure to translate research advances into production-ready solutions
• Participate in code review processes to maintain research code quality, catching subtle issues including those arising from AI-assisted code generation
• Instrument experiments with appropriate logging, monitoring, and evaluation pipelines to ensure reproducibility and reliability of research outcomes
• Contribute to the research community through open-source releases, technical documentation, and knowledge sharing within the team

Minimum Qualifications:

• 2+ years of experience designing, training, and evaluating machine learning models using deep learning frameworks such as PyTorch or JAX
• Experience with Reinforcement Learning and/or Large Language Models (LLMs), including areas such as RLHF, policy optimization, or LLM fine-tuning
• Experience implementing and iterating on ML experiments end-to-end, from data pipeline construction through model evaluation and analysis
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment

Preferred Qualifications:

• Demonstrated ability to contribute to open-source ML research codebases or reproducible research artifacts
• Experience applying ML research to large-scale production systems, including familiarity with A/B experimentation frameworks and staged rollout practices
• Experience training or fine-tuning large-scale foundation models, including familiarity with distributed training techniques such as model parallelism or mixed-precision training
• First-author or significant contributions to publications at peer-reviewed ML conferences such as NeurIPS, ICML, ICLR, CVPR, or EMNLP
• Interest or expertise in formal mathematics and theorem proving tools such as Lean

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 WhatsApp 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.

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.