Microsoft Research AI Frontiers lab is seeking applications for the position of Senior Researcher – Foundations of Generative AI to join their team in New York, NY.

The mission of the AI Frontiers lab is to expand the pareto frontier of Artificial Intelligence (AI) capabilities, efficiency, and safety through innovations in foundation models and learning agent platforms. Some of our projects include work on small language/action models (e.g., Phi, Orca, Fara-7B), new architectures and optimizers (e.g., Belief State Transformer, Dion), and agentic AI systems (e.g. AutoGen, MagenticOne, OmniParser).

We are seeking a Senior Researcher – Foundations of Generative AI to join our team and lead efforts in discovering and building the foundations of generative AI through representations and objectives. As a Senior Researcher – Foundations of Generative AI, you will play a crucial role in leading, developing, improving, and exploring new architectures, representations, and learning objectives that unlock new capabilities and/or scalability. Your work will have a significant impact on the development of cutting-edge technologies, advancing the state-of-the-art, and providing practical solutions to real-world problems.

Our ongoing research areas encompass but are not limited to:

• New architectures and learning methodologies to enable always-on, proactive agents
• Test time training to support infinite context windows
• Active visual reasoning for orders-of-magnitude faster image processing/encoding
• World models of user/system interactions to enable imagination rollouts and search
• Multi-scale temporal reasoning and planning in transformer models
• Continual learning and adaptation methods that operate at human speed
• New multimodal model architectures and training methods for Vision-Language (VLM) and Vision-Language-Action (VLA) models
• Proactive, real-time agents for computer use, racing, and gaming

The Microsoft Research AI Frontiers lab offers a vibrant environment for cutting-edge, multidisciplinary research, including access to diverse, real-world problems and data, opportunities for experimentation and real-world impact, an open publication policy, and close links to top academic institutions around the world. 

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

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• Apply research and engineering skills to develop, prototype, and evaluate cutting-edge research ideas.
• Work closely with other researchers and engineers to rapidly prototype and test new research ideas, driving a high-impact agenda and publishing results where appropriate.
• Collaborate hands-on with other researchers, engineers, and internal and external product groups to deliver high-impact solutions to real-world problems.
• Embody our culture and values

• Doctorate (or currently pursuing) in Computer Science or relevant field
  • OR  equivalent experience.

Preferred Qualifications

• Doctorate in Computer Science or relevant field AND 2+ years related research experience
  • OR  equivalent experience.
• Research program demonstrated by public artifacts like models, tools, code in the AI space or publications at the following conferences: NeurIPS, ICML, ICLR, ACL, NAACL, CVPR, COLT, ECCV, ICCV, EMNLP.
• 2+ years of academic or industry experience in developing, applying, and/or implementing algorithms for machine learning/statistics, using common ML engineering programming languages and platforms such as Python, Python numerical libraries, PyTorch, TensorFlow and/or HuggingFace.
• Experience publishing academic papers as a lead author or essential contributor in a top AI conference or journal.
• Deep understanding of frontier model architectures, especially transformers and state space models
• Hands-on experience building and working with Large Language Models (LLMs) or multimodal models (VLMs, VLAs), including pre-training, fine-tuning, and inference
• 2+ years of industry or academic experience with building, debugging and optimizing large-scale ML training pipelines.
• Demonstrated software engineering excellence building and deploying prototypes, applications, or open-source (OSS) technologies. Providing a link to a GitHub profile and/or code samples on your CV/resume, is highly encouraged.
• Ability to work independently and ramp-up quickly on complex projects or unfamiliar code
• Ability to collaborate, communicate effectively, and work as part of a multi-disciplinary team
• Keen interest in real-world applications and impact.

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