AI Research Scientist, SysML
Meta

Job Info

Meta is seeking an AI Research Scientist to join Fundamental AI Research (FAIR). We are committed to advancing the field of artificial intelligence by making fundamental advances in technologies to help interact with and understand our world. We are seeking individuals passionate in solving systems challenges in areas such as deep learning, computer vision, audio and speech processing, and natural language processing. Our researchers have opportunities to make core algorithmic and system advances and apply their ideas at an unprecedented scale.An ideal candidate for FAIR's Systems and Machine Learning (SysML) team will have an exceptional research and industry experience working on efficiently scaling training and inference systems to unlock new AI capabilities. The mission of SysML is to unlock the potential of AI technologies by innovating in AI systems towards Usability, Efficiency, and Sustainability. We aim to sustainably accelerate machine learning innovations with novel system solutions and advance AI infrastructures at scale.

AI Research Scientist, SysML Responsibilities:

• Perform cutting-edge research to advance the science and technology of machine learning systems
• Develop highly scalable, efficient learning algorithms based on state-of-the-art machine learning and neural network methodologies
• Design and adapt neural network architectures for state-of-the-art parallel, distributed systems
• Develop novel architectures, evaluation methodology and benchmarks to quantitatively assess quality of solutions
• Contribute research that leads to innovations in: resource-efficient AI data and algorithm scaling and neural network architectures, memory and energy-efficient AI systems, environmentally-sustainable AI system and hardware designs
• Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results
• Publish research results and contribute to research that impacts Meta product development

Minimum Qualifications:

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• Ph.D. in Computer Science or related quantitative field with 5+ years of industry or relevant experience
• Proven knowledge of machine learning and deep learning systems
• Proficiency in PyTorch and GPU programming
• Experience with performance analysis and optimization for CPUs, GPUs, and state-of-the-art AI systems
• Experience with memory and energy-efficient AI systems, environmentally-sustainable AI system designs, or AI-driven system optimization
• Proven track record of achieving significant results as demonstrated by publications at leading conferences such as NeurIPS, ICML, ICLR, MLSys, ISCA, ASPLOS, CGO, PLDI, PACT, HPCA, MICRO, or similar.
• Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward

Preferred Qualifications:

• Experience developing AI algorithms or AI-System infrastructure in C/C++, Rust, or Python
• Experience with distributed systems or on-device algorithm development
• Proven technical expertise in ML system architectures and technologies
• Experience developing and optimizing systems for at-scale machine learning execution
• Experience devising data-driven models and real-system experiments and design implementation for AI system optimization
• Effective leadership and communication skills

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