Senior Machine Learning Developer I

BCE Inc.; Mississauga; Hybrid; CAD 120,000 - 180,000; Full time

Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

Bell service discounts

Job summary

Bell is seeking a Senior ML Developer to join our AIOps Platform team in Mississauga. You will work with Data Scientists to take AI/ML solutions to production, accelerating delivery of core AI services from PoC to highly available, production‑grade systems.

You will bridge data science and platform operations, applying robust software engineering, intent‑driven development, and MLOps best practices to ensure scalable, reliable, and performant systems.

Qualifications

• Bachelor's degree in Computer Science or Computer Engineering or related field.
• 5+ years of professional software engineering experience, focused on production‑grade AI/ML systems.
• Expert‑level proficiency in Python.
• Strong experience with the GCP stack (Vertex AI, BigQuery, Spanner, GKE, GCS, Pub/Sub).
• Deep practical knowledge of MLOps best practices and taking models from PoC to production.
• Hands‑on experience with real‑time data processing (Apache Beam, Dataflow) and event‑driven architecture (Kafka, PubSub).
• Proven ability in Infrastructure as Code (Terraform/CDKTF) and cloud‑native orchestration (Kubernetes).
• Strong software‑testing and quality discipline (unit/integration/end‑to‑end/functional testing).
• Hands‑on experience with ML frameworks such as PyTorch, scikit‑learn, XGBoost, or TensorFlow.
• Experience with graph databases / Spanner Graph and Graph Neural Networks (GNN).
• Strong communication, analytical, debugging, and cross‑functional collaboration skills.

Responsibilities

• Production ML Engineering: Collaborate with data science, platform developers and architects to operationalize ML models and workflows.
• MLOps & Lifecycle Management: Own the end‑to‑end ML lifecycle (feature engineering, training, evaluation, deployment).
• Pipeline & Architecture Design: Build real‑time streaming pipelines and robust event‑driven architectures.
• Design and build high‑throughput, low‑latency system architectures with deduplication.
• API & Service Delivery: Lead API and schema design for complex ML‑enabled services.
• Quality & Reliability: Emphasize testing, code reviews, and security checks across the team.
• Infrastructure Management: Implement Infrastructure as Code (Terraform/CDKTF) for cloud deployments.

Skills

Python

GCP stack

MLOps

Real-time processing

Kubernetes

Testing discipline

AI/ML frameworks

Education

Bachelor's degree in Computer Science or Computer Engineering

Tools

Apache Beam/Dataflow

Kafka

Pub/Sub

Terraform/CDKTF

Kubernetes

Spanner Graph

Job description

Select how often to receive alerts (in days): Create alert

At Bell, we do more than build world‑class networks, develop innovative services and create original multiplatform media content – we advance how Canadians connect with each other and the world.

If you’re ready to bring game‑changing ideas to life and join a community that values, professional growth and employee wellness, we want you on the Bell team.

The Bell Mobility team offers the best and latest mobile devices, wireless services and Internet of Things solutions to consumer and business customers, with the top speeds, coverage and reliability on Canada’s Best National Network. We love to innovate, embrace big challenges, and live for the newest technology

Summary

We’re looking for a Senior ML Developer to join our AIOps Platform team. In this role, you will work closely with Data Scientists to take AI/ML solutions to production. You will accelerate the delivery of our core AI services from proof‑of‑concept to highly available, production‑grade. You will bridge the gap between data science and platform operations, applying robust software engineering practices, intent‑driven development, and MLOps best practices to ensure our systems are scalable, reliable, and performant.

Key Responsibilities

• Production ML Engineering: Collaborate with data science, platform developers and architects, and other teams to operationalize ML models, LLM / Agentic workflows, and advanced analytics.
• MLOps & Lifecycle Management: Own the end‑to‑end ML lifecycle (feature engineering, training, evaluation, deployment). Enforce MLOps best practices including CI/CD, model versioning, reproducibility, and rollout controls.
• Pipeline & Architecture Design: Build real‑time streaming pipelines using Apache Beam/Dataflow and design robust event‑driven architectures (Kafka/PubSub patterns).
• Design and build high‑throughput, low‑latency system architectures with strict idempotency and deduplication.
• API & Service Delivery: Lead API and schema design for complex ML‑enabled services.
• Quality & Reliability: Instill a strong testing and quality mindset across the team (test‑driven development, unit/integration tests, code reviews, security checks). Debug and optimize distributed systems for maximum performance.
• Infrastructure Management: Implement Infrastructure as Code (Terraform/CDKTF) to manage scalable, cloud‑native deployments.
  

Critical Qualifications

• Bachelor's degree or higher in Computer Science or Computer Engineering or a related field. Relevant experience may be considered in lieu of a degree.
• 5+ years of professional software engineering experience, specifically focused on production‑grade AI/ML systems.
• Expert‑level proficiency in Python software engineering.
• Strong experience with the GCP stack (Vertex AI, BigQuery, Spanner, GKE, GCS, Pub/Sub).
• Deep practical knowledge of MLOps best practices and taking models from proof‑of‑concept to highly available production services.
• Hands‑on experience with real‑time data processing (Apache Beam, Dataflow) and event‑driven architecture (Kafka, PubSub).
• Proven ability in Infrastructure as Code (Terraform/CDKTF) and cloud‑native orchestration (Kubernetes).
• Strong software‑testing and quality discipline (unit/integration/end‑to‑end/functional testing, code review, security checks)
• Hands‑on experience with ML frameworks such as PyTorch, scikit‑learn, XGBoost, or TensorFlow.
• Experience with graph databases / Spanner Graph and Graph Neural Networks (GNN)
• Strong communication, analytical, debugging, and cross‑functional collaboration skills.
• Ability to write clean, efficient, and reusable code.
• Plus if you have experience with distributed / federated query engines such as Trino.

Preferred Qualifications

• Experience with telecom industry data and network architecture.
• Post‑secondary degrees or certificates in Statistics, Mathematics, and Data Science.
• Experience deploying secure agentic workflows with cost management and decision traceability.

#LI-SS1

Adequate knowledge of French is required for positions in Quebec.

Additional Information:

For work arrangements that are ‘Hybrid’, successful candidates must be based in Canada and report to a set Bell office for a minimum of 3 days a week. Recognizing the importance of work‑life balance, Bell offers flexibility in work hours based on the business needs.

We know that caring for our team members is at the heart of a healthy, positive and thriving workplace. As part of our team, you’ll enjoy a comprehensive compensation package that includes a competitive salary and a wide range of benefits to support the well‑being of you and your family. As soon as you join us, you'll be eligible for medical, dental, vision and mental health benefits that you can tailor to your specific needs. Plus, as a Bell team member, you'll enjoy a 35% discount on our services and access exclusive offers from our partners.

At Bell, we are proud of our focus on fostering an inclusive and accessible workplace where all team members feel valued, respected, supported, and that they belong.

Bell is committed to clarity in our hiring process. All roles posted are opportunities we’re actively recruiting for, unless stated otherwise. We also want to make sure that everyone has an equal opportunity to join our team. We encourage individuals who may require accommodations during the hiring process to let us know. For a confidential inquiry, email your recruiter or [e-mail] to make arrangements. If you have questions or feedback regarding accessibility at Bell, we invite you to complete the Accessibility feedback form or visit our Accessibility page for other ways to contact us.

Artificial intelligence may be used to assess parts of your application. Please review our privacy policy ( see Phenom for details ) to learn more about how we collect, use, and disclose your personal information.