1 day ago
Mississauga, CanadaSenior
Responsibilities
- Collaborate with data scientists, platform developers, architects, and other teams to operationalize ML models, LLM/agentic workflows, and advanced analytics.
- Own the end-to-end ML lifecycle, including feature engineering, training, evaluation, deployment, model versioning, reproducibility, and rollout controls.
- Build real-time streaming pipelines with Apache Beam and Dataflow and design event-driven architectures using Kafka and Pub/Sub patterns.
- Design high-throughput, low-latency, idempotent, and deduplicated distributed systems.
- Lead API and schema design for complex ML-enabled services.
- Apply testing, code review, security, debugging, and performance-optimization practices.
- Implement Infrastructure as Code with Terraform/CDKTF for scalable cloud-native deployments.
Requirements
- Bachelor’s degree or higher in Computer Science, Computer Engineering, or a related field; relevant experience may substitute for a degree.
- At least 5 years of professional software engineering experience focused on production-grade AI/ML systems.
- Expert-level Python software engineering proficiency.
- Strong experience with GCP services including Vertex AI, BigQuery, Spanner, GKE, GCS, and Pub/Sub.
- Practical experience with MLOps and taking models from proof of concept to highly available production services.
- Hands-on experience with Apache Beam, Dataflow, Kafka, Pub/Sub, Terraform/CDKTF, and Kubernetes.
- Strong software-testing and quality discipline covering unit, integration, end-to-end, and functional testing, code review, and security checks.
- Experience with PyTorch, scikit-learn, XGBoost, or TensorFlow.
- Experience with graph databases or Spanner Graph and Graph Neural Networks.
- Strong communication, analytical, debugging, coding, and cross-functional collaboration skills.
- Preferred experience includes telecom data and network architecture, post-secondary study or certificates in Statistics, Mathematics, or Data Science, secure agentic workflows, and distributed or federated query engines such as Trino.
- Adequate knowledge of French is required for positions in Quebec.
Benefits
- Hybrid work arrangement based in Canada, with at least three days per week in a Bell office in Mississauga or Don Mills, Ontario.
- Regular full-time employment with flexible work hours based on business needs.
- Medical, dental, vision, and mental health benefits available upon joining.
- 35% discount on Bell services and access to exclusive partner offers.
- Inclusive and accessible workplace with hiring-process accommodations available.
Tech Stack
Apache BeamApache KafkaGoogle BigQueryGoogle Cloud PlatformKubernetesPythonPyTorchscikit-learnTensorFlowTerraformXGBoost