As Microsoft continues to push the boundaries of AI, we are on the lookout for individuals to work with us on the most interesting and challenging AI questions of our time. Our vision is to build systems that have true artificial intelligence across agents, applications, services, and infrastructure. We aim to make AI accessible to all , consumers, businesses, developers , so that everyone can realize its benefits.
Job Summary
We are seeking a Senior Machine Learning Engineer to join the Growth Intelligence team and contribute to the evolution of Copilot, our personal AI assistant. In this role, you will design and build models and ML pipelines for user and conversation understanding , helping Copilot better interpret user intent, extract meaning from conversations, and deliver more relevant, personalized experiences.
Responsibilities
- Build and deploy machine learning models for natural language understanding tasks including intent detection, topic classification, conversation summarization, and user personas.
- Design ML pipelines to architect scalable, production-grade training and inference pipelines using Spark, Databricks, Azure ML, and modern ML frameworks.
- Develop and fine-tune transformer-based models and text encoders; build and maintain embedding pipelines and vector databases for semantic search and retrieval.
- Drive rigorous offline and online experimentation to measure model quality, iterate on architectures, and improve key product metrics.
- Collaborate with data engineers, data scientists, and product teams to translate research insights into shipped features and align model outputs with product goals.
- Show ownership mindset by proactively monitoring model performance in production, diagnosing regressions, and addressing scalability and reliability challenges before they become bottlenecks.
- Contribute strategically by identifying opportunities to improve model architectures, training methodologies, and evaluation frameworks; mentor others on ML best practices.
Qualifications
- Bachelor's degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field, and 4+ years of related experience.
- Master's degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field, and 3+ years of related experience.
- Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field, and 1+ year of related experience.
- Proven experience in NLP, including experience with modern transformer architectures for tasks such as classification, encoding, summarization, and semantic search.
- Experience with text embedding models, vector databases, and retrieval-augmented generation (RAG) patterns.
- Familiarity with distributed training, model optimization, and serving ML models at scale.
- Experience with search ranking, relevance modeling, or information retrieval systems.
- Proficiency in Python and ML frameworks such as PyTorch, Hugging Face Transformers, or similar.
- Experience working with data platforms (e.g., Spark, Databricks, Azure ML) and building end-to-end ML pipelines from data ingestion through model deployment.
Required Skills
- NLP
- Machine Learning
- Python
- PyTorch
- Hugging Face Transformers
- Spark
- Databricks
- Azure ML
- Text Embedding Models
- Vector Databases
- Retrieval-Augmented Generation (RAG)
- Distributed Training
- Model Optimization
- Serving ML Models at Scale
- Search Ranking
- Relevance Modeling
- Information Retrieval Systems
Preferred Skills
- None
XML job scraping automation by YubHub
