Job Location: Noida
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.
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.
Responsibilities
Applied ML @ Microsoft
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 demonstrate strong program management expertise to be able to multi-task effectively. You will lead a team of data scientists effectively to deliver success. You will lead a team of ML scientists and engineers to translate business and functional requirements into concrete deliverables including the design, development, testing & deployment of highly scalable distributed ML services. You will provide thought leadership to scientists and engineers to help invent and implement scalable models while building tools. This is a unique high visibility opportunity to drive significant business impact, deep-dive into large-scale problems and enable measurable action as via experiments. We are particularly interested in candidates who have experience building and working with distributed systems.
You will work with teams of talented ML scientists and attract best scientists in ML.
# Represent MCDS to various personas across data scientists to the C-suite across Microsoft and externally
# Lead proof-of-value and quantify business impact
# Seek, give and receive critical feedback including but not limited to code review
# Ensure results and retention of the team conducting regular 1x1s, team meetings, providing feedback, coaching & delegation
# Collaborate with business stakeholders to ensure ML solutions successfully deliver the business outcomes
# Excellent Program Management & organizational abilities
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
Qualifications
Masters degree in Computer Science, Mathematics, Statistics, Physics or related field. Focus on ML preferred. Ph.D. desirable.
12+ Years of experience in ML, Deep Learning in industry/academia
6+ Years of experience recruiting and managing Ph.D. level scientist, researchers and engineers
6+ Years of experience recruiting and managing Ph.D. level scientist, researchers and engineers
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
# 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
# Proficient in Relational Databases (SQL) and Big Data (Hive, PySpark, ..)
# Exposure to real-world MLOps
# Knowledge of working in cloud-computing environment like Azure or AWS or Google Cloud. (Azure preferred)
# Exposure to real-world MLOps
# Knowledge of working in cloud-computing environment like Azure or AWS or Google Cloud. (Azure preferred)
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
# 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
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.
Learn more about us at: https://medium.com/data-science-at-microsoft
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
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