L4 Data Management (AI/ML Specialist / Developer) - Network Automation

Our team and what we'll accomplish together

Join TELUS Technology's Network Automation and Intelligence team, where we're revolutionizing how Canada's leading telecommunications network operates. We're a dynamic group of software developers and network specialists who are building the intelligent, self-healing network of tomorrow. Our mission? To leverage cutting-edge AI and machine learning to predict network issues before they happen, optimize performance in real-time, and deliver exceptional experiences to millions of Canadians.

As part of our team, you'll be at the intersection of telecommunications and artificial intelligence, working on problems that directly impact network reliability, efficiency, and innovation. We're not just maintaining infrastructure—we're building intelligent systems that learn, adapt, and evolve. Your work will power everything from predictive maintenance algorithms that prevent outages to ML models that optimize network traffic across our national infrastructure. If you're passionate about applying AI to solve real-world problems at massive scale, this is where you belong.

What you'll do

• Design and develop end-to-end ML/AI pipelines that process terabytes of network telemetry data to predict failures, optimize performance, and automate network operations
• Build and optimize robust ETL/ELT workflows using GCP tools (Dataflow, Dataproc, Cloud Composer) to ingest, transform, and prepare network data from diverse sources for ML model training and inference
• Implement and maintain AI integration protocols including MCP (Model Context Protocol) servers to enable seamless communication between AI models and network data sources, tools, and external systems
• Collaborate with network engineering teams, data scientists, and platform architects to identify automation opportunities and translate business requirements into scalable AI solutions
• Create and deploy production-grade machine learning models for network anomaly detection, capacity forecasting, and intelligent routing optimization
• Develop standardized protocols and APIs for AI model serving, ensuring efficient context sharing and tool integration across distributed network automation systems
• Partner with DevOps and MLOps teams to implement CI/CD pipelines for model deployment, monitoring, and continuous improvement in GCP environments
• Build data quality frameworks and monitoring systems to ensure the reliability and accuracy of data flowing through our ML pipelines
• Drive the adoption of best practices in feature engineering, model versioning, experiment tracking, and protocol-based AI integrations across the network automation domain
• Analyze complex network datasets using advanced statistical methods and ML techniques to uncover insights that inform strategic network planning decisions
• Support the migration and modernization of legacy data systems to cloud-native architectures, ensuring scalability and performance
• Influence technical strategy by staying current with emerging AI/ML technologies, protocols, and recommending innovative approaches to network automation challenges

What you bring

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Engineering, or related technical field
• 3+ years of hands-on experience developing and deploying machine learning models in production environments
• Deep understanding of ML/AI concepts including supervised/unsupervised learning, deep learning, time-series forecasting, and anomaly detection
• Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, scikit-learn, XGBoost)
• Proven experience designing and implementing ETL/ELT pipelines for large-scale data processing
• Solid expertise with GCP services including BigQuery, Cloud Storage, Vertex AI, Dataflow, Pub/Sub, and Cloud Functions
• Experience with SQL and NoSQL databases (BigQuery, Cloud SQL, Firestore, or similar)
• Strong understanding of data modeling, data warehousing concepts, and dimensional modeling
• Knowledge of API design, RESTful services, and communication protocols for AI/ML systems
• Demonstrated ability to write clean, maintainable, production-quality code with proper testing and documentation
• Excellent problem-solving skills with the ability to translate complex business problems into technical solutions

Great-to-haves

• Experience implementing MCP (Model Context Protocol) servers or similar AI integration protocols for context management and tool orchestration
• Familiarity with telecommunications networks, network protocols (SNMP, NetFlow, gRPC), or infrastructure monitoring systems
• Knowledge of MLOps practices and tools (Kubeflow, MLflow, Airflow) for model lifecycle management and real-time streaming data processing in network environments

Location: Anywhere in Canada #LI-Remote