Machine Learning Engineer

Role – ML Engineer

Role Overview:

YOE: 5+

Work Mode: 4+1

Hybrid Number of Openings: 1

Key Responsibilities

•Design, deploy, and support machine learning and AI solutions in production, SLA-driven managed services environments

•Provide operational support for AI platforms including incident response, troubleshooting, and root cause analysis

•Monitor AI and ML model performance, data quality, and drift; implement retraining and optimization strategies

•Build and maintain MLOps pipelines supporting model training, validation, deployment, and rollback

•Develop and support AI workloads using Microsoft Azure AI, Azure Machine Learning, Azure OpenAI, and Copilot extensibility

•Design, train, and optimize virtual assistants enterprise workflows

•Implement and support AI capabilities including Predictive Intelligence, Virtual Agent, and AI Search

•Collaborate with service desk, engineering, security, and platform teams to drive automation and continuous service improvement

•Act as a technical escalation point for AI-related client issues and enhancement requests

•Contribute to AI innovation initiatives, proofs of concept, and reusable solution patterns within Bell Techlogix

Required Qualifications

•Bachelor's degree in Computer Science, Data Science, Machine Learning, or equivalent practical experience

•5+ years of experience in machine learning engineering, AI development, or applied data science

•Strong proficiency in Python, SQL, and API-based integrations

•Hands-on experience supporting machine learning models in production environments

•Experience working in managed services, consulting, or enterprise IT environments

•Strong understanding of cloud platforms (Microsoft Azure preferred)

Preferred Qualifications

•Experience with Azure Machine Learning, Azure AI Services, or Azure OpenAI

•Hands-on experience with Kore.ai XO Platform or enterprise conversational AI

•Experience implementing or supporting ServiceNow AI/ML, Predictive Intelligence, or Virtual Agent

•Familiarity with MLOps, CI/CD pipelines, Infrastructure as Code (Terraform, Bicep, ARM)

•Knowledge of Responsible AI, data governance, and enterprise security practices

•Relevant certifications (Microsoft, ServiceNow, Kore.ai)