Machine Learning Lead
2 weeks ago
Description :
2) Build innovative products and propositions backed with problem solving mindset to discover and solve latent needs of customers.
3) Build Embedded Finance (Banking as a Service) applications.
4) Ensure designs are highly available, highly modular, highly scalable and highly secure and Drive digital business .
Education : Masters or Undergraduate in Computer Science/Electrical/Civil/Mechanical.
Experience : 6 - 8 years of overall industry experience, with at least 3 - 4 years in Machine Learning (ML)/MLOps, or Business Rule Engine (BRE) implementation.
Technical Expertise :
1) ML/MLOps System Design : Proven experience in end-to-end ML/MLOps system architecture including model/BRE implementation (batch/API/cloud), debugging, and production maintenance.
2) Programming & Data Tools : Proficient in Python, PySpark, NumPy, Pandas, SQL, and Linux. Good to have Koalas, Dask.
3) Cloud & Big Data : Hands-on experience with Azure cloud services including Azure Databricks, Spark, Data Warehousing, and pipeline orchestration.
4) CI/CD & DevOps : Skilled in Azure DevOps for CI/CD pipeline setup and management, including automated model deployment.
5) API Development : Experience with FastAPI/Flask for building scalable ML models APIs.
6) Exposure to credit risk modeling and financial services is a strong plus.
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