Specialist - Industrial IoT

Job Summary Job Description MLOps Engineer Experience -7 Years Location -Bellandur bangalore Shift-1.30pm- 10.30pm Key Skills – MLOps, CI/CD, GIT hub, Python, Ansible, Azure DevOps. Hands on experience in object oriented and/or functional programming using Python • Proven experience delivering and supporting production scale ML systems • Hands on exposure to computer vision and/or cognitive services within production AI solutions • Ability to assess and apply machine learning techniques to solve real business problems • Experience integrating ML models on unstructured data as part of enterprise AI workflows MLOps & ML Platform Engineering • Design, implement, and maintain end to end MLOps frameworks covering: o Model training o Experiment tracking o Versioning and reproducibility o Deployment and monitoring o Automated retraining workflows • Implement and operationalize MLflow or equivalent frameworks for experiment tracking and lifecycle management • Build custom APIs for ML model training and inference, supporting both batch and real time workloads Cloud Native & Containerized ML Systems • Develop cloud first solutions using Microsoft Azure, including: o Azure Machine Learning o Azure Fabric (as applicable) • Hands on experience building and deploying ML pipelines using Azure Machine Learning SDK • Design and manage containerized ML workloads using: o Docker o Kubernetes • Orchestrate large scale ML/DL workloads, including distributed training and massively parallel model execution on cloud infrastructure Data, Scale & Performance Engineering • Proficient in orchestrating large scale ML and DL jobs using big data tooling and modern container orchestration platforms • Experience with model optimization and hyperparameter tuning at scale for ML/DL models • Working knowledge of mathematics and algorithms, including: o Linear algebra o Probability o Statistics • Strong understanding of data engineering tools and patterns, including: o Databricks o Apache Spark o Azure Data Factory Collaboration & Communication • Ability to engage effectively with technical experts and stakeholders at all organizational levels • Strong capability to identify opportunities where ML and analytics can: o Improve business workflows Enable data driven decision making • Excellent written and verbal communication skills, with the ability to convey complex technical concepts clearly and concisely !-- [if !supportLineBreakNewLine]--> !--[endif]-->