Job Description

Ottawa,Ontario,Canada
Job ID

768623

Grow with us

About the Opportunity

We are seeking a Data Engineer with deep hands-on experience to help us build and scale AI solutions across our organization. You will work closely with Radio experts and product teams to identify impactful AI/ML use cases, develop robust models, and deploy them into production. This role is ideal for someone who thrives on building end-to-end ML systems in a technically strong but AI-new environment.
What you will do:
Collaborate with domain experts to uncover, prioritize, and prototype AI/ML opportunities aligned with business goals. Evaluate data availability, quality, and infrastructure readiness for proposed use cases. Design and implement proof-of-concept models to validate value and technical feasibility. Architect and implement scalable ML solutions, deeply integrated with robust and reliable data pipelines. Own the complete ML lifecycle: data ingestion, preprocessing, feature engineering, model design, training, evaluation, deployment, and monitoring. Design and optimize data architectures supporting both batch and streaming ML use cases. Collaborate with data engineering teams to build real-time and batch pipelines using managed streaming platforms such as Kafka or equivalent technologies. Guide the development and automation of ML workflows using modern MLOps and CI/CD practices. Support the development and testing of AI solutions using Microsoft AI platforms, including Azure AI services. Assist in the integration of AI tools such as Azure AI Foundry, Microsoft Copilot Studio, or Glean into real-world workflows. Help build and refine internal tools or web-based interfaces related to AI applications. Stay up to date with emerging trends in AI and proactively contribute ideas for innovation and improvement. Champion responsible AI practices including model governance, explainability, fairness, and compliance.
What you will bring:
5+ years of experience in Machine learning, Applied AI, or data science with a proven record of delivering ML systems at scale. 2+ years of experience in data engineering or building ML-supportive data infrastructure and pipelines. Advanced degree in Electronics Engineering, Computer Engineering, Data Engineering, Machine Learning, or a related technical field. Proficient in Python, with experience in Java and C++ for backend or performance-critical tasks. Deep expertise with ML frameworks (TensorFlow, PyTorch, JAX) and cloud platforms, especially AWS (SageMaker, Lambda, Step Functions, S3, etc.). Experience with managed streaming data platforms for real-time ML data pipelines. Experience with distributed systems and data processing tools such as Spark, Airflow, and AWS Glue. Fluency in MLOps best practices, including CI/CD, model versioning, observability, and automated retraining pipelines. Strong leadership skills with experience mentoring engineers and influencing technical direction across teams. Excellent collaboration and communication skills, with the ability to align ML strategy with product and business needs.

Preferred Skills

Experience working in Telecom, Embedded systems, or Radio software domains. Familiarity with AI/ML technologies relevant to telecom, such as: Time series forecasting Anomaly detection Reinforcement learning
What happens once you apply?