Senior Machine Learning Engineer – Action Models and Generative AI – Microsoft Research AI Frontiers

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Microsoft Research AI Frontiers lab is seeking applications for the position of Senior Machine Learning Engineer – Action Models and 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, generative AI, and learning agent platforms. Some of our projects include work on language models (e.g., Phi, Orca), action models (e.g., for racing, gaming, and office productivity), multi-agent systems (e.g. AutoGen), and evaluation (e.g., Eureka).

We are seeking a Senior Machine Learning Engineer to join our team and advance the state-of-the-art in foundation models and Generative AI for actions and behavior. Our domains of interest include: web/OS agents, gaming agents, and real-time control for racing. Our ongoing research areas include but are not limited to:

• Novel architectures and representations for efficient and generalizable learning of action models
• Multi-scale temporal reasoning and planning in transformer models
• Pre-training methods for video generation and world modeling
• Continual learning and adaptation at human speed
• Specializing models to capture individual human behavior and style
• Steering models towards specific behaviors via natural language instruction

As a Senior Machine Learning Engineer on our team, you will work hands-on on challenging and impactful projects. You will apply your engineering skills and expertise to a range of problems including rapid prototyping and testing of research hypotheses, contributing to, releasing, and maintaining high-quality open-source models and frameworks, and building and deploying robust practical solutions to real world problems. Additionally, you will collaborate closely with other researchers, engineers, and product teams across the company to amplify your impact and grow your career in a supportive and stimulating environment.

Microsoft Research 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.

In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

Required Qualifications

• Bachelors in Computer Science or relevant field AND 4+ years technical engineering experience with coding in languages including, but not limited to, Python, C, C++, C#, or Java
  • OR equivalent experience.
• 4+ years of industry or academic experience in applying, implementing, and/or developing algorithms for machine learning, artificial intelligence, or statistics.
• 2+ years of industry or academic experience with common ML engineering programming languages and platforms such as Python, Python numerical libraries, PyTorch, TensorFlow and/or Hugging Face.
• 2+ years of industry or academic experience with building, debugging and optimizing large, high performance ML training pipelines.

Preferred Qualifications

• Masters in Computer Science or relevant field AND 6+ years technical engineering experience with coding in languages including, but not limited to, Python, C, C++, C#, or Java
  • OR Doctorate (or currently pursuing) in Computer Science or relevant field AND 2+ years technical engineering experience as above
  • OR equivalent experience.
• Demonstrated software engineering excellence building and deploying prototypes, applications, or open-source (OSS) technologies. Providing a link to a GitHub profile (if available) and/or code samples, is highly encouraged.
• Deep understanding of deep learning model architectures, especially transformers and state space models.
• Hands-on experience building and working with large foundation models such as Large Language Models (LLMs), Large action models (LAMs), or multimodal models, including pre-training, fine-tuning, and inference.
• Experience using and supporting ML infrastructure including job schedulers, big data storage, low latency interconnects, and large clusters of Graphics Processing Units (GPUs).
• Experience with high-frequency simulation environments such as for gaming or racing.
• Experience publishing academic papers at relevant conferences and journals (such as NeurIPS, ICML, ICLR, AAAI, ACL).
• Ability to work independently and ramp-up quickly on complex, unfamiliar code.
• Ability to collaborate, communicate effectively, and work as part of a multi-disciplinary team.
• Keen interest in real-world applications and impact, and/or experience working in a commercial software product team.

Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

Microsoft will accept applications for the role until September 29, 2025.

#Research

• Apply Machine Learning (ML) engineering skills to build, test, and deploy robust and scalable AI-based technologies, libraries, and applications.
• Work closely with researchers and engineers to rapidly prototype and test new AI research ideas, driving a high-impact agenda and publishing results where appropriate.
• Collaborate hands-on with other researchers, engineers, and internal and external product group partners on high-impact projects that deliver real-world impact to people and society.
• Embody our culture and values.