Member of Technical Staff, AI Pre-Training
5 Months ago • All levels
Job Description
Contribute to the development of one of the world's best foundational AI models at Microsoft AI. The Pre-Training team focuses on challenging deep learning problems at scale. Responsibilities include developing algorithms, model architectures, and data mixtures for large-scale training; conducting experiments and overseeing flagship training runs; collaborating with infrastructure, data, and post-training teams; and using a data-driven approach grounded in meticulous ablations. Successful candidates will have expertise in deep learning, strong analytical skills, experience with large-scale distributed systems, and a collaborative work style.
Must Have:
- Expertise in deep learning
- Strong analytical skills
- Experience with large-scale distributed systems
- Data-driven approach
- Collaborative work style
Help deliver one of the best foundational models in the world at Microsoft AI.
At Microsoft AI, we are on a mission to train the world’s most capable AI frontier models, pushing the boundaries of scale, performance and product deployment. The Pre-Training team at Microsoft AI tackles some of the most challenging problems in deep learning at scale. As a team, we will deliver one of the best foundation models in the world, forming the foundation of many initiatives across Microsoft AI.
We are looking for outstanding individuals excited about contributing to the next generation of systems that will transform the field. We are looking for candidates who:
- Have proven expertise in areas of interest, evidenced by an exceptional publication track record and significant technical leadership in high-impact projects
- Exhibit strong analytical skills, attention to detail, and a commitment to data-driven decision-making
- Have experience and/or in-depth understandings about large-scale distributed systems
- Demonstrate an ability to work collaboratively in a fast-paced, innovative environment
- Develop algorithms, model architectures, data mixtures, and scaling laws for large-scale training using a rigorous data-driven approach grounded in meticulous ablations
- Drive algorithmic implementations, conduct experiments, and oversee flagship training runs on our in-house large-scale distributed stack
- Collaborate closely with teams on infrastructure, data, post-training, and multimodality
- Embody our and .
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