Description

Meta's Fundamental AI Research (FAIR) organization is seeking a Research Engineer to drive advancements in generative models. The role involves working across the full spectrum of research, engineering, and optimization for frontier model efforts.

Research Engineer, Fundamental AI Research (FAIR) - Generative Models/LLM Acceleration Responsibilities:

• Innovate, lead, and execute pioneering algorithmic research to push the state-of-the-art in generative models and LLM performance
• Directly contribute to the experimental process, including designing details, implementing reusable code, running evaluations, and organizing results
• Collaborate with cross-functional teams (research, product, infra) to build new and advance LLM optimization
• Analyze and optimize code for quality, efficiency, and performance, and provide feedback to peers during code reviews
• Lead initiatives, provide technical guidance and mentorship to peers, and help onboard new team members
• Take a significant role in components, features, or systems with good end-to-end understanding
• Contribute to publications, open-sourcing initiatives, and mentor other team members

Minimum Qualifications:

• Master's degree or higher in a relevant technical field (e.g., Computer Science, Machine Learning, AI, or related discipline)
• 6+ years of experience in machine learning, deep learning, or AI research, or equivalent practical experience
• Experience designing and implementing large-scale model training pipelines using frameworks such as PyTorch or JAX
• Experience with distributed computing and parallel training techniques including data parallelism, model parallelism, or pipeline parallelism
• Experience debugging and optimizing AI systems for performance, reliability, and correctness across the full model lifecycle

Preferred Qualifications:

• Experience building evaluation frameworks and benchmarking pipelines to measure model quality and capability regressions
• Experience with large language model pretraining, fine-tuning, post-training, or inference optimization
• Track record of contributions to peer-reviewed AI research publications or open-source AI frameworks

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.