
Applied Scientist II
- Noida, Uttar Pradesh
- Permanent
- Full-time
- Applied Research & Development: Contribute to the design and implementation of machine learning models and algorithms for search, summarization, and content understanding in Office applications.
- Model Development: Build and fine-tune ML/DL models using frameworks like PyTorch or TensorFlow. Collaborate on deploying models in production environments with a focus on scalability and performance.
- Cross-Functional Collaboration: Work closely with engineering, product, and research teams to translate business needs into technical solutions and deliver impactful features.
- Experimentation & Evaluation: Conduct experiments, analyze results, and iterate on solutions to improve precision, recall, and user satisfaction.
- Innovation: Stay current with research trends in generative AI and NLP. Explore new signals, data sources, and modeling techniques to evolve intelligent systems and contribute to the Copilot ecosystem.
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research)
- OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
- OR equivalent experience.
- 2+ years of industry experience in applied machine learning or data science roles.
- Proficiency in Python and ML libraries such as PyTorch or TensorFlow.
- Experience developing and evaluating generative AI models.
- Familiarity with NLP techniques and content understanding.
- Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
- Solid verbal and written communication skills to explain complex technical concepts to diverse audiences.
- Ability to tackle open-ended problems and deliver practical, scalable solutions.
- Experience deploying ML models in production environments.
- Exposure to full product lifecycle from prototyping to deployment and iteration.
- Contributions to research publications, patents, or open-source projects.