Principal Researcher - CoreAI

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The Microsoft CoreAI Modeling team develops advanced AI technologies that integrate language and multi-modality for various Microsoft products. We built models for internal and external applications, focusing on post-training OpenAI models, OSS models through large-scale continual pre-training, and RL, as well as code-specific models such as SWE.

We are seeking a Principal Researcher - CoreAI with expertise and experience in large-scale modeling training and data curation. You will work on LLMs, SLMs, multimodal systems, and coding models using proprietary and open-source frameworks.

This will include managing the full model pipeline from dataset ingestion to training, evaluation, and inference.

Our team operates like a startup, emphasizing efficiency and hands-on problem-solving. Applicants must write code, debug training jobs, and document their learning experiences.

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/Minimum Qualifications

• Doctorate in relevant field AND 5+ years related research experience
  • OR equivalent experience.
• 2+ years of experience in machine learning, deep learning, or multimodal research (e.g., language-vision integration, cross-modal learning)

Other Requirements:

Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings:

• Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Preferred/Additional Qualifications

• Extensive experience with foundation models, including large-scale training, model inference, reinforcement learning, reasoning models, vision-language integration, and audio-visual modeling
• Hands-on experience with large-scale distributed training or serving, and systems thinking
• Proficiency in programming languages such as Python, and experience with machine learning frameworks like PyTorch and Triton
• Experience working with large, complex datasets and developing data pipelines for LLM training
• Demonstrated ability to collaborate within interdisciplinary teams and communicate complex, multimodal research concepts effectively

Research Sciences IC6 - The typical base pay range for this role across the U.S. is USD $163,000 - $296,400 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 $220,800 - $331,200 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 posts positions for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

#CoreAI

#AIPlatform

• Design and evolve our distributed-training platform that supports LLMs, SLMs, multi-modal, code and open-source models.
• Write production-grade code that automates data preprocessing, sharding, checkpointing, mixed-precision & pipeline parallelism.
• Profile and monitoring end-to-end training runs, eliminate bottlenecks, tune kernels, and devise new scheduling and placement strategies.
• Data preparation, training, and evaluation of customization tasks.
• Collaboration with Microsoft product groups to integrate multimodal AI solutions across applications.
• Staying updated with the latest advancements in deep learning, inference optimization, and multimodal learning.
• Collaborate with top students and interns with opportunity to publish great work to community.
• Embody our Culture and Values