Microsoft is a company where passionate innovators come to collaborate, envision what can be and take their careers to levels they cannot achieve anywhere else. This is a world of more possibilities, more innovation, more openness in a cloud-enabled world. The Business & Industry Copilots group is a rapidly growing organization that is responsible for the Microsoft Dynamics 365 suite of products, Power Apps, Power Automate, Dataverse, AI Builder, Microsoft Industry Solution and more. Microsoft is considered one of the leaders in Software as a Service in the world of business applications and this organization is at the heart of how business applications are designed and delivered.

We are looking for an Applied Scientist to join our team!

This is an exciting time to join our group and work on something highly strategic to Microsoft. Microsoft Dataverse is the platform to securely store an enormous amount of data in a cost efficient, scalable and easily manageable way. This team builds a suite of microservices to get near real-time insights over your data in Microsoft AI ERP. You will be a part of a team of engineers who thrive on solving complex problems at scale while doing it with impeccable quality.

An ideal candidate has prior expertise in generative AI, software engineering skills, technical aptitude, communication skills and a collaborative working style. The scientist should focus on evaluation metrics to make purpose-built LLMs to infuse AI in productivity scenarios. Additionally, they should be comfortable with the end-to-end ML/AI solutions development process, starting from understanding the customer business problem and ending with production implementation of machine learning pipelines. As part of the role, they will also work with a globally diverse team of applied scientists and engineers who are building AI platforms, models and products. They are expected to drive growth mindset and embrace the rapidly evolving innovations and breakthroughs in this field.

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.

• Educational Background:

• Bachelor’s, Master’s, or Ph.D. degree in Computer Science, Electrical Engineering, or other related technical fields (e.g., mathematics, physics, statistics, or similar).

• Experience:

• 3+ years of experience working with machine learning libraries to solve real world data science problems

• Skills:

• Proficiency in Python, scripting, AI efficiency tools.

• Experience in large language model architectures (e.g. Transformer, etc).

• Strong foundation in classical machine learning techniques and statistics.

• Prior experience in model and experimental evaluations like A/B testing, shadow testing etc.

• Experience handling real-world noisy data.

• Demonstratable experience with software engineering principles, parallel/distributed computing, and cloud technology platforms (e.g. Azure etc.)

• Proficiency with object-oriented programming practices.

• Problem-Solving:

• Ability to understand complex business contexts and solve open-ended problems.

• Proactive mindset focused on optimizing solutions for business impact.

• Design, plan, and execute experiments to evaluate models, datasets, and metrics for product impact.

• Define, evaluate, and assess evaluation metrics, including fairness and bias, contributing to ethical AI and privacy policies.

• Document results/progress and share findings to promote innovation.

• Conduct model and experimental evaluations including A/B testing, shadow testing, and other validation techniques.

• Implement and fine-tune neural network architectures, including transformer-based models.

• Work on frontier models to push AI innovation boundaries.

• Partner with research teams to integrate cutting-edge ML technologies into products.

• Collaborate with product and platform teams to design AI-powered experiences.

• Build and deploy ML models, develop data pipelines, and manage training/test datasets.

• Work collaboratively with cross-geo teams at flexible hours while fostering a healthy and inclusive environment.