Job Description

Are you an applied scientist with a passion for applying state-of-the-art AI innovations to augment human creativity? Join us as we grow the M365 Copilot Create ML team, where we are revolutionizing visual creation within the M365 Copilot, Microsoft Designer, Photos. Located in Noida, we're pushing the limits of machine learning to help create information workers to create the world's best designs.
As a Senior Applied Scientist in the Create ML team, you will work in an exciting and fast-paced environment, collaborating closely with teams across the company, including Microsoft Research and various product groups. You will have the opportunity to develop cutting-edge visual creation models and build top tier visual creation experience in M365 Copilot. This role is crucial for driving innovation and creating modern, inclusive, and intelligent design experiences used by millions worldwide.
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.
Responsibilities:

• You will work on machine learning (ML) projects across various domains like natural language processing (NLP), Vision and harness LLMs, VLMs, and Diffusion models to deliver visual AI solutions for our customers.
• You will get the opportunity of working in a fast-paced environment developing algorithms and techniques leveraging text, and images for analyzing and transforming content to build solutions that have the potential to transform people's lives.
• You will work with engineering partner teams on the model integration/flight/maintenance.

Qualifications:
Required Qualifications:

• Bachelor's Degree in Statistics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)

• OR Master's Degree in Statistics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research)

• OR Doctorate in Statistics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)

• OR equivalent experience.

• Proficiency in Python and relevant ML libraries (e.g., PyTorch).

• Experience with LLM/VLM/diffusion models (e.g., GPT, Deepseek-R1, Stable diffusion, Phi-V, Qwen).

• Technical background in coding and design, specifically in the development of AI models for scaled production services.

• Demonstrated success in shipping applied research to production, highlighting a track record of combining coding skills with advanced expertise in AI model development.

Preferred Qualifications:

• Problem solving and data analysis skills, with expertise in developing or applying predictive analytics, statistical modelling, data mining, or machine learning algorithms.
• Leadership skills to influence others, with the ability to understand team dynamics, retain, attract, and develop team members.
• Grounded in growth mindset, and advocate for diversity and inclusion.
• Customer obsessed and passionate about product impact.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the .