
Eligibility Criteria
Currently pursuing a PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, Electrical Engineering, Computer Engineering, Econometrics, or a related technical field; must have at least one semester/quarter remaining after the internship; strong research experience in ML, Deep Learning, NLP, Computer Vision, Generative AI or related areas; proficient in Python and ML frameworks such as PyTorch or TensorFlow; experience designing experiments, statistical analysis, and handling large datasets; minimum CGPA/percentage of 7.5/70% (or equivalent) is preferred; no backlog allowed at the time of joining.

Job Description & Key Responsibilities
Microsoft is a global technology leader that empowers every person and organization on the planet to achieve more. With a presence in more than 190 countries, Microsoftβs research labs and product teams drive breakthroughs in cloud computing, artificial intelligence, gaming, and productivity software. In India, the company has a strong engineering ecosystem spanning Bengaluru, Hyderabad, and other tech hubs, offering a vibrant mix of multicultural teams, cuttingβedge infrastructure, and a culture of continuous learning. Interns at Microsoft are treated as full contributors; they get access to the same tools, mentorship, and impact opportunities as regular employees, making the internship a launchpad for a future career in technology.
The Applied Sciences Internship is designed for PhD candidates who want to translate advanced research into realβworld products. As an Applied Science PhD Intern, you will work sideβbyβside with senior researchers, software engineers, and product managers to build AIβdriven solutions that improve Microsoftβs services. You will be responsible for endβtoβend development of machineβlearning pipelines, from data ingestion and cleaning to model training, evaluation, and deployment. The role offers exposure to largeβscale data platforms, cloud services, and the latest generativeβAI frameworks, allowing you to see how academic breakthroughs become features used by millions.
Key responsibilities include:
1. Design, implement, and evaluate machineβlearning and AI solutions for realβworld product scenarios.
2. Analyse and optimise the performance of advanced algorithms on largeβscale datasets.
3. Translate business and product challenges into research problems and experimental frameworks.
4. Conduct rigorous experiments to assess model effectiveness and drive continuous improvement.
5. Develop, train, fineβtune, and evaluate Large Language Models (LLMs) and Small Language Models (SLMs).
6. Build scalable prototypes and AIβpowered systems ready for production deployment.
7. Prepare, clean, and analyse massive datasets while ensuring data quality and integrity.
8. Innovate new approaches for model evaluation, benchmarking, and performance optimisation.
9. Collaborate with crossβfunctional teams to integrate research breakthroughs into Microsoft products.
10. Document findings, contribute to technical reports, publications, patents, or openβsource projects.
Tech stack: Python, PyTorch/TensorFlow, Azure Machine Learning, SQL/NoSQL databases, Git, Docker/Kubernetes, and familiarity with largeβscale data processing tools such as Spark. The internship can lead to fullβtime research or engineering roles within Microsoft Research, Azure AI, or product groups, offering a clear growth path from intern to senior researcher or principal engineer. Joining Microsoft gives you access to worldβclass mentorship, a collaborative culture that values curiosity, and the chance to work on products that impact billions of users worldwide.