Applied Scientist II

Encontrado en: beBee S CL - hace 1 mes


Chile Microsoft A tiempo completo

Overview

MSAI organization plays a key role in Microsoft to build products that help boost Enterprise users’ productivity. We help users find relevant artifacts and get their daily jobs done in timely and efficient manner. MSAI is now responsible to deliver M365 Chat which is designed to help users find, summarize, act upon their work data in an interactive pattern.

As an Applied Scientist specializing in ranking recommendation ML models, you will play a pivotal role in shaping the future of our ranking systems ( across different enterprise data like Emails, Documents, Calendar, Graph connectors etc). You will collaborate closely with cross-functional teams to design, implement, and evaluate state-of-the-art algorithms that power our cross entity ranking engine. Leveraging your expertise in machine learning, you will drive innovation and continuously improve the performance and relevance of our retrieval stack. 

#MSAI #M365Core

Qualifications

Requirements:

Ph.D. or Master's degree in Computer Science, Electrical Engineering, Statistics, or 4+ years of related field expereince with a focus on machine learning, information retrieval, or recommender systems. 

Proven track record of research and practical experience in developing and deploying ranking recommendation ML models and LLMs in real-world applications.

Preferred Qualifications: 

Machine Learning 

Responsibilities

Role Responsibilities: 

Research and develop novel ML algorithms and techniques to enhance the ranking accuracy and effectiveness of retrieval systems – which in turn gets fed into LLMs for response generation. Design and implement scalable and efficient algorithms for large-scale ranking tasks, considering factors such as user engagement, diversity, and fairness.  Conduct rigorous experiments and analysis to evaluate the performance of ranking models, identify areas for improvement, and iterate on existing solutions.  Collaborate with software engineers and data engineers to integrate ML models into production systems and optimize their performance.  Stay abreast of the latest advancements in machine learning, information retrieval, and recommendation systems, and contribute to the company's intellectual property through patents and publications.  Provide technical leadership and mentorship to junior team members, fostering a culture of innovation, collaboration, and continuous learning.  Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.Industry leading healthcareEducational resourcesDiscounts on products and servicesSavings and investmentsMaternity and paternity leaveGenerous time awayGiving programsOpportunities to network and connect
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