ML Ops Engineer

 Job Description

Location: Bangalore ( ascendion locations)

• 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 ML initiatives with overall business goals.
• Implement scalable and efficient machine learning systems. Collaborate with software engineers to integrate ML 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.

Python and SQL Hands-on Coding experience