Senior Machine Learning Developer I

Bell; Montreal (administrative region); Hybride; CAD 110 000 - 170 000; Plein temps

Avantages offerts par ce poste

Medical, dental, vision & mentalhealth

Bell service discount 35%

Hybrid work arrangement

Inclusive, accessible workplace

Résumé du poste

Bell is seeking a Senior ML Developer to join the AIOps Platform team. You will work with Data Scientists to bring AI/ML solutions to production, accelerating delivery from proof‑of‑concept to highly available services.

You’ll bridge data science and platform operations with robust software engineering, intent‑driven development, and MLOps best practices. You’ll collaborate to operationalize ML models, build real‑time pipelines, design scalable architectures, and own end‑to‑end ML lifecycle with

Qualifications

• Bachelor's degree in Computer Science or Computer Engineering or related field (or equivalent experience).
• 5+ years of production‑grade software engineering, AI/ML systems.
• Expert-level Python engineering.
• Strong GCP experience: Vertex AI, BigQuery, Spanner, GKE, GCS, Pub/Sub.
• Deep MLOps knowledge: lifecycle, CI/CD, versioning, reproducibility, rollout controls.
• Hands-on with real-time data processing (Beam/Dataflow) and event‑driven architecture (Kafka/ Pub/Sub).
• IaC expertise (Terraform/CDKTF) and cloud‑native orchestration (Kubernetes).
• Strong testing and quality discipline; ML frameworks like PyTorch, scikit‑learn, XGBoost, TensorFlow.
• Experience with graph databases/Spanner Graph and Graph Neural Networks (GNN).
• Excellent communication and cross‑functional collaboration.
• Nice to have distributed/federated query engines like Trino.

Responsabilités

• Operationalize ML models and AI/LLM workflows with teams.
• Own end‑to‑end ML lifecycle: features, training, evaluation, deployment.
• Enforce MLOps: CI/CD, versioning, reproducibility, rollout controls.
• Design real‑time pipelines and robust event‑driven architectures.
• Lead API and schema design for ML‑enabled services.
• Promote testing, code reviews, and security checks across the team.
• Manage infrastructure as code to support scalable deployments.

Connaissances

Python

GCP stack

ML frameworks (PyTorch, TensorFlow)

Apache Beam/Dataflow

Kafka/PubSub

Kubernetes

Terraform/CDKTF

CI/CD

Data processing

Graph databases/Spanner Graph

Formation

Bachelor's degree in Computer Science or Engineering

Outils

Terraform/CDKTF

Kubernetes

Apache Beam

Dataflow

BigQuery

Spanner Graph

Description du poste

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.

Adequate knowledge of French is required for positions in Quebec.

Additional Information

Position Type: Management

Job Status: Regular - Full Time

Job Location: Canada : Ontario : Mississauga || Canada : New Brunswick : Moncton || Canada : Ontario : Don Mills || Canada : Quebec : Montreal

Work Arrangement: Hybrid

Application Deadline: 10/16/2026

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.

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