AI Research Scientist, SysML – FAIR

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Company Overview
A leading global technology organization is seeking AI Research Scientists to join its Fundamental AI Research (FAIR) team. The organization is dedicated to advancing artificial intelligence through open science innovations, building scalable machine learning systems, and optimizing AI infrastructures for usability, efficiency, and sustainability. FAIR’s mission is to push the state of AI research and deliver transformative impact at unprecedented scale across multiple modalities including images, video, text, and audio.

Summary
The AI Research Scientist, SysML, will conduct cutting-edge research to advance machine learning systems, infrastructure, and AI system design. This role focuses on developing scalable, resource-efficient, and environmentally sustainable AI systems, contributing to both foundational research and practical implementations at large scale.

Responsibilities

• Conduct research to advance the science and technology of machine learning systems
• Perform research that enables learning the semantics of data across modalities (images, video, text, audio)
• Contribute to innovations in scalable ML systems, resource-efficient AI data and algorithm scaling, neural network architectures, and memory- and energy-efficient AI system design
• Develop data-driven models to optimize AI system design and performance
• Collaborate with researchers and cross-functional teams to communicate research plans, progress, and results
• Publish research findings and contribute to work that impacts product development
• Enable distributed training at scale through improvements in training libraries and components (e.g., cuBLAS, cuDNN, FlashAttention)
• Optimize training performance via hardware-software co-design and system-level innovations

Minimum Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, or a relevant technical field, or equivalent practical experience
• PhD in Computer Science, Computer Engineering, or a relevant technical field with 2+ years of equivalent domain-specific industry experience
• Experience in systems, computer architectures, compiler and programming languages, machine learning, and AI
• Proficiency in Python, C++, C, Rust, or similar languages and experience with PyTorch
• Experience developing and optimizing systems for large-scale machine learning execution
• Skilled in devising data-driven models, real-system experiments, and AI system optimization
• Knowledge of scalable ML systems, efficient AI data and algorithm scaling, and neural network architectures
• Strong problem-solving abilities and experience evaluating alternative solutions and trade-offs
• Experience working and communicating effectively in cross-functional teams

Preferred Qualifications

• Proven track record of impactful research, grants, patents, or publications at top-tier conferences and workshops such as MLSys, ISCA, ASPLOS, HPCA, PLDI, CGO, NeurIPS, ICML, ICLR, or equivalent
• Demonstrated research and software engineering expertise via work experience, coding competitions, or contributions to widely used open-source repositories (e.g., GitHub)

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