Collaborate with Data Scientists to test and scale new algorithms through pilots and later industrialize the solutions at scale to the comprehensive fashion network of Customers.
Influence, build, and maintain the large-scale data infrastructure required for the AI projects, and integrate with external IT infrastructure/service to provide an e2e solution.
Develop common components to address pain points in machine learning projects, like model lifecycle management, feature store, and data quality evaluation.
Provide input and help implement framework and tools to improve data quality?
Work in cross-functional agile teams of highly skilled software/machine learning engineers, data scientists, designers, product managers, and others to build the AI ecosystem within Customer’s org.
Deliver on time, demonstrating a strong commitment to delivering on the team mission and agreed-on backlog.
Required Qualifications/Skills
Bachelor's degree in Computer Science, Information Technology, or related field.
Experience in having handled ML-specific requests and/or solution build for startups.
Understanding of, or curiosity to ramp up on, Azure AI infrastructure, platform, and services on L300-400.
Understand and deep dive into ML pipeline, ML Ops, and data ingestion as it refers to Azure ML.
Experience with AI services like Azure OpenAI Service on L400 and consulting with startups about fine-tuning, simple prompt engineering, etc
Good knowledge of ML pipeline in terms of data set size, intensive training, compute involved, etc, to have a planning discussion with the startup.