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 workflowsEnable data driven decision making
• Excellent written and verbal communication skills, with the ability to convey complex technical concepts clearly and concisely