Senior Machine Learning Engineer

2 weeks ago

Noida, Uttar Pradesh, 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 Qualifications -

Total 8+ years of relevant experience Depth in Data Science, Generative AI and Engineering Background in machine learning, deep learning, computer vision and multimodal learning Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch) to develop production-grade quality product Experience with distributed systems design and implementation Proficiency in Agile development practices and Continuous Integration/Continuous Deployment (CI/CD) Experience with vision models, diffuser models, multimodal models. Some examples are ViT, DeiT, BEiT, DINO, DINOv2, SAM, Stable diffusion, CLIP, BLIP, LLaVA etc. Excellent problem-solving skills and the ability to work independently and collaboratively Good understanding of statistics, linear algebra, and probability theory Familiarity with cloud platforms (e.g., Azure, AWS, GCP) and distributed computing

Preferred Qualifications -

Preferred training & fine-tuning experience on large data Preferred experience with audio, NLP algorithms

#AIPlatformHiring

Responsibilities

As a (Senior) Machine Learning Engineer in our team, you will:

Collaborate with researchers and data scientists to design sophisticated machine learning models Implement and fine-tune neural network architectures, including transformer-based models Optimize model performance, scalability, and efficiency Conduct experiments to evaluate model performance, robustness, and generalization Explore novel techniques and approaches to enhance model capabilities Stay up to date with the latest advancements in Computer Vision, Multimodal, deep learning, and AI research Work with large-scale datasets, preprocess them, and create appropriate data representations Select relevant features and ensure data quality for training and evaluation Collaborate with cross-functional teams, including researchers, software engineers, and product managers Communicate technical findings and insights effectively Deploy trained models in production environments Monitor model performance, troubleshoot issues, and iterate on improvements 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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