Job Description

We are building a planet-scale multi-modal database from the ground up. You will be part of the team that is reimagining the databases in the era of Large Language Models (LLMs) by deeply integrating Artificial Intelligence (AI) into all parts of the stack.

As a

Principal Machine Learning Engineer

, you will lead and collaborate with a team of passionate engineers, driving ideas to impactful results in a fast-paced environment. You will work on designing, building, and deploying large-scale machine learning systems, with an emphasis on production-grade solutions involving data pipelines, distributed training, model serving, and performance optimization. You are experienced in machine learning engineering from ideation and algorithm selection, to architecture and implementation, to deployment and continuous improvement.

Successful engineers in our team have problem solving, design, coding and debugging skills, drive for execution and results, rigor in delivering quality software and a desire for continuous learning. Our team values a friendly, collaborative atmosphere with a passion for technology, and we believe that a diverse team with diverse perspectives that applies empathy and uses great communication skills helps deliver superior products and is key to success. This is a great opportunity to challenge yourself, grow your career, and influence the next generation of computing at Microsoft.

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.

Responsibilities

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Develop and deploy scalable Machine Learning models. Develop robust evaluation frameworks to assess model performance, conduct systematic benchmarking, and address identified weaknesses while ensuring compliance with customer standards. Defines the vision and strategy for collaboration efforts between researchers and development teams at the individual product level. Brings new technology and approaches into production by applying long-term research efforts to solve immediate product needs. Drives high-stakes negotiations across teams to ensure cutting edge technology is being applied to products in a practical way that meets key business objectives. Ensures that teams apply an understanding of research approaches used across and outside of the company to leverage (and not re-invent) solutions. Represents the organization across the company. Incorporates key business and product requirements to define a clear agenda and vision that influences the direction of the company/products and provides a competitive or strategic advantage. Drives programs structured around the specificity of key business challenges. Provides strategic direction for the kinds of data used to solve problems. Embody our culture and values.

Qualifications

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Required Qualifications:

Bachelor's Degree in Computer Science, Machine Learning or Artificial Intelligence, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research) + OR Master's Degree in Computer Science, Machine Learning or Artificial Intelligence, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
+ OR Doctorate in in Computer Science, Machine Learning or Artificial Intelligence, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research)
+ OR equivalent experience.
Proven experience training large-scale modern Machine Learning (ML) models (e.g., transformers, diffusion models, foundation models). Hands-on experience in key model optimization techniques (e.g., mixed precision training, distributed training, fine-tuning, RLHF, LoRA). Familiarity with model evaluation, data curation pipelines, and reproducible research practices.

Preferred Qualifications

Master's Degree in Computer Science, Machine Learning or Artificial Intelligence, or related field AND 12+ years related experience (e.g., statistics, predictive analytics, research) + OR in Computer Science, Machine Learning or Artificial Intelligence, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research)
+ OR equivalent experience.
Deep understanding of modern deep learning frameworks such as PyTorch or TensorFlow, and scalable training infrastructure. First-author publication in top-tier machine learning conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR, ACL).



Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.