MLOps Developer (Azure / Databricks / MLflow), energy sector, Montreal (hybrid)

Abbeal; Montreal; Híbrido; CAD 90.000 - 130.000; Jornada completa

Descripción de la vacante

Abbeal is seeking an MLOps developer to industrialize and operate classic, generative and agentic AI solutions on Azure and Databricks for a major public energy player in Quebec. Montreal-based with hybrid work depending on the mandate; deliverables in French.

You will implement MLflow pipelines, model registries and deployment, and lead CI/CD, IaC, and security practices across the ML lifecycle.

Formación

• Experience with MLflow for experiment tracking, model registry, packaging and deployment.
• Experience building training, validation, batch and real-time inference pipelines.

Responsabilidades

• MLOps, LLMOps and AgentOps practices: CI/CD, automation, infrastructure as code, environment management.
• Pipeline instrumentation and monitoring.
• Security, traceability, secrets management, quality controls.
• Reusable libraries, templates and accelerators.

Conocimientos

Python / PySpark

MLflow

Herramientas

Terraform

Descripción del empleo

Industrialize classic, generative and agentic AI solutions on Azure and Databricks for a major public energy player in Quebec.

• MLflow
• Python / PySpark
• Terraform

Context

A major public energy player in Quebec is launching a multi-year AI services program through a North American integration partner. In this context, we are looking for an MLOps developer to industrialize and operate classic, generative and agentic AI solutions on Azure and Databricks.

Your missions

• Experiment tracking, model registry, packaging and deployment with MLflow
• Training, validation, batch and real-time inference and deployment pipelines
• MLOps, LLMOps and AgentOps practices: CI/CD, automation, infrastructure as code, environment management
• Pipeline instrumentation and monitoring
• Security, traceability, secrets management, quality controls
• Reusable libraries, templates and accelerators

Terms

Montreal, hybrid depending on the mandate. Day schedule. Working language for deliverables: French. Mandate executed under a multi-year framework agreement, duration and start date per statement of work.