Design, implement, and optimize machine learning algorithms and models.– Neural networks (Graph neural network), Deep learning & transformers (Temporal Fusion Transformer ), NLP, gradient boosting using open source machine learning frameworks – tensorflow, pytorch, XGBoost, LightbGM
Enable functionality to support analysis, model optimization, statistical testing, model versioning, deployment and monitoring of model and data.
Ability to translate functionality into scalable, tested, and configurable platform architecture and software.
Establish strong software engineering principles for development in Python on the Azure Kubernetes Platform.
Strong ownership of deliverables, with design decisions aligned to scale and industry best practices.
Collaborate with cross-functional teams to align Client initiatives with overall business goals.
Implement scalable and efficient machine learning systems. Collaborate with software engineers to integrate Client models into production systems.
Work closely with data engineers to ensure the availability and quality of data for training and evaluation of machine learning models.
Develop strategies for deploying machine learning models at scale. Ensure models are integrated into production systems with high reliability and performance.
Design and conduct experiments to evaluate the performance of machine learning models. Iterate on models based on feedback and evolving business requirements.