Senior Machine Learning Engineer

4 weeks ago


Hyderabad, India Microsoft Full time
Overview

Within AI Platform, the Azure ML team enables data scientists and developers to quickly and easily build, train, deploy, manage, and consume machine learning models.

Qualifications

Required Qualification:Total 8+ years of relevant experienceDepth in Data Science, Generative AI and EngineeringBackground in machine learning, deep learning, and natural language processingProficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch) to develop production-grade quality productExperience with distributed systems design and implementationProficiency in Agile development practices and Continuous Integration/Continuous Deployment (CI/CD)Experience with transformer-based and diffuser-based models (e.g., BERT, GPT, T5, Llama, Stable diffusion)Good understanding of statistics, linear algebra, and probability theory.Familiarity with cloud platforms (e.g., Azure, AWS) and distributed computingExcellent problem-solving skills and the ability to work independently and collaborativelyPreferred Qualifications:Preferred training & fine-tuning experience on large data#IDCAIPlatformHiring

Responsibilities

As a (Senior) Machine Learning Engineer in our team, you will:Collaborate with researchers and data scientists to design sophisticated machine learning modelsImplement and fine-tune neural network architectures, including transformer-based modelsOptimize model performance, scalability, and efficiencyConduct experiments to evaluate model performance, robustness, and generalizationExplore novel techniques and approaches to enhance model capabilitiesStay up to date with the latest advancements in NLP, deep learning, and AI researchWork with large-scale datasets, preprocess them, and create appropriate data representationsSelect relevant features and ensure data quality for training and evaluationCollaborate with cross-functional teams, including researchers, software engineers, and product managersCommunicate technical findings and insights effectivelyDeploy trained models in production environmentsMonitor model performance, troubleshoot issues, and iterate on improvementsBenefits/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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