Microsoft Data & Applied Scientist II 

Spain, Catalonia, Barcelona 

307105668

Azure AI Search provides a secure, at scale, search engine over user-owned data. The data and applied science team develops the machine learning components that power the search engine, both for traditional and generative AI scenarios such as RAG (retrieval-augmented generation). Our goal is to deliver high quality search results for very different industries, corpus sizes and scenarios, and our work includes multiple aspects, among which:

• Training and fine-tuning of deep learning models, including language models, often with tight latency constraints;
• Collection, generation and filtering of training and evaluation data;
• Metrics development;Keeping up with research and industry trends.

Here is an example of our work:

Required Qualifications:

• Bachelors, Masters or advanced degree in Computer Science or related field (including Mathematics and Physics).
• Relevant industry experience in applying Machine Learning techniques.
• Relevant experience in coding in Python, C#, Java or C++  .

Preferred Qualifications:

• MS or PhD in computer science or related field.
• Experience with machine learning frameworks such as PyTorch, ONNX, etc...
• Experience with deep model training and evaluation.
• Experience with using large language models.
• Customer focused, strategic, drives for results, is self-motivated, and has a propensity for action.
• Problem solver: ability to solve problems that the world has not solved before.

As part of the team, you will be responsible for different aspects, such as:

• Train, fine-tune, domain adapt and distill large scale NLP models for real-world large-scale applications;
• Work on the full lifecycle of machine learning development, including training data collection, model training, component and end-to-end evaluation;
• Design and get high quality labels for a wide range of techniques (retrieval, ranking, machine reading comprehension etc.);
• Select, develop and build metrics to use across the full range of search engine components;
• Incorporate customer feedback into evaluations and models development;
• Contribute to experimentation infrastructure and proofs-of-concept to test out new ideas and concepts;
• Understand existing code and write new code that is efficient and readable;
  Partner effectively with program management, engineers, and other functions across products;
• Document work and communicate in a clear and efficient way.