Microsoft Cloud & AI group has a unique opportunity at the intersection of cloud computing and AI. We are disrupting the cloud industry with innovation and large-scale AI implementation
Part of the Cloud & AI engineering organization, Microsoft Cloud Data Sciences (MCDS) fosters a data driven culture. DSaaS (Data Sciences as a Service) Innovation Operations Center is a shared service within MCDS that drives impact and innovation using state-of-the-art Machine Learning (ML).
In DSaaS, we drive applied ML across Customer, Partner, Field & Cloud. We work across groups : engineering, Sales, Cloud Marketplace, Partner, Digital, Marketing, Support, Developer Relations, Start-ups and Finance.
Most of our models are deployed into production systems including our MLOps platform. We have a strong presence in internal and external ML conferences & journals.
We are looking for ML scientists / ML engineers with a strong background in machine learning to build industry-leading solutions.
You will work with huge volumes of data to solve / enable solving real-world ML problems that are productionized into our MLOps platform to be consumed by downstream applications OR become product feature OR stand-alone products.
You will work with global teams with an opportunity to create phenomenal impact.
You will combine data sciences depth, programming expertise and mathematical understanding of techniques to deliver state-of-the-art ML solutions for problem solving across the enterprise.
You will demonstrate a product mindset and look to deliver re-usable components that can be deployed as or into ML services / productized solutions.
You will partner closely with engineering, product management, analytics & transformation teams from across MCDS to deliver outstanding value to stakeholders and our products.
The candidate must demonstrate the following :
Strong expertise in Python programming and one of the Deep Learning frameworks (PyTorch, MXNet, TensorFlow, Keras)
Knowledge of (with deep expertise in at-least three of) Classification, Prediction, Recommender Systems, Time Series Forecasting, Anomaly Detection, Optimization, Graph ML, NLP
Hands-on develop ML models using the above techniques across Customer, Partner, Field & Sales in varied domains
Ability to both use existing libraries (ML, Deep Learning, Re-inforcement Learning) as well as design algorithms ground-up
Able to prepare data pipelines and feature engineering pipelines to build robust models using SQL, PySpark, Azure Data Studio etc
Strong research record preferred demonstrated, through publications
Scientific thinking and ability to invent : Prior experience creating intellectual property through patents desirable.
Demonstrate strong program management expertise to be able to multi-task effectively
Lead / Mentor a team of data scientists effectively to deliver success; Mentor junior data scientists effectively
Running end-end data sciences projects from a conceptualization to completion
Able to present to stakeholders effectively about the findings & also iterate on the business problem definition & experimentation
Be a Team Player. Apart from working cross-functionally effectively, contribute to peer reviews, team learning, meet product objectives and develop best practices for the organization.
We are looking to strengthen our ML footprint across Digital namely e-commerce / direct (BizApps Direct business around PowerApps & Dynamics Platform), Developer Relations, Learning Portal, Marketplace.
Prior experience in organizations driving e-commerce ML solutions like recommender system design, User Insight Engine Development, Personalization Engines, Digital Buyer Journey, next Best Action, Marketing Channel Optimization is highly desired.
Knowledge of client-side scripted web-analytics tools like Adobe (across the suite) is highly valuable.
Masters degree in Computer Science, Mathematics, Statistics, Physics or related field. desirable
Following are desirable :
Proficient in Relational Databases (SQL) and Big Data Technologies (Hive, PySpark, ..)
Exposure to real-world MLOps
Knowledge of working in cloud-computing environment like Azure or AWS or Google Cloud. Azure preferred.
8+ Years of Experience in ML, Deep Learning in industry / academia
Join us to be part of an iterative & fast-paced environment where you can drive impact, innovation and apply state-of-the-art techniques to solve problems on a global scale.
Join our exciting data sciences team that is shaping the evolution of Cloud & AI. Learn more about us at : style "margin : 0px;">