Senior AI/ML Platform Engineer

Jarvis Consulting Group; Toronto; Hybrid; CAD 110,000 - 150,000; Full time

Job summary

A leading consulting group in Toronto seeks a Senior AI/ML Platform Engineer to lead MLOps pipeline implementations using Azure and Databricks. This role involves collaborating with data teams to ensure efficient deployment and monitoring of machine learning models, focusing on high performance and security. Ideal candidates possess a strong background in software and data engineering, with proven experience in managing MLOps processes.

Qualifications

• 5+ years of experience in software engineering, data engineering, or DevOps.
• At least 2+ years in MLOps roles.
• Hands-on experience with Azure services and Databricks.

Responsibilities

• Design end-to-end MLOps pipelines using Azure Machine Learning and Databricks.
• Collaborate with teams to automate model training, validation, deployment, and monitoring.
• Monitor ML services in production and enhance performance.

Skills

Communication skills

Stakeholder management

Feature Engineering

Python

Education

Bachelor’s or Master’s degree in Computer Science, Engineering

Tools

Azure Machine Learning

Databricks

MLflow

Azure DevOps

Azure Kubernetes Service (AKS)

Terraform

Job description

Direct message the job poster from Jarvis Consulting Group

Technology Talent Advisor | HeadHunter | Executive Search | Tech Enthusiast | Leader / Mentor

Job Title: Senior AI/ML Platform Engineer

Location: Toronto, ON (Hybrid - 2 days in office)

Job Type: Contract (6 months to start - extendable)

About Us:

Jarvis is driven by a bold vision to transform the professional services landscape by setting a new standard for innovation, empowerment, and impactful solutions in data, AI, and technology. Our unwavering dedication is rooted in propelling businesses toward sustained success while making a positive impact on communities. Strategically operating from Toronto and Montreal, Europe, and North Africa, Jarvis extends its services across Canada and the US. Our diverse team comprises expert advisors and forward-thinking technologists who work tirelessly to unlock the full potential of businesses, ensuring the consistent delivery of exceptional results. The world of technology is rapidly evolving through innovation and cutting-edge technologies. As we move into the future, we believe in keeping up with relevant technologies and building that future ourselves. Our greatest assets are our people, and at Jarvis, we value imagination and curiosity as much as capability and skill.

Job Summary:

For our Technology Advisory Services division, we are seeking a highly skilled and experienced Senior AI/ML Platform Engineer to lead the design, development, and implementation of scalable MLOps pipelines on Azure and Databricks. This role will focus on optimizing the lifecycle of machine learning models — from development to deployment and monitoring — while ensuring high availability, performance, and security.

Key Responsibilities:

• Design and implement end-to-end MLOps pipelines using Azure Machine Learning, Databricks, MLflow, and related tools.
• Collaborate with Data Scientists, Engineers, and DevOps teams to automate model training, validation, deployment, and monitoring processes.
• Build scalable data pipelines and integrate feature engineering workflows in Databricks.
• Set up model versioning, testing, and CI/CD workflows for ML artifacts.
• Ensure security, compliance, and governance standards are met across all ML operations.
• Monitor and troubleshoot ML services in production, and proactively enhance performance and reliability.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 5+ years of experience in software engineering, data engineering, or DevOps with at least 2+ years in MLOps roles.
• Strong hands-on experience with Azure services such as Azure Machine Learning, Azure DevOps, Azure Data Lake, and Azure Kubernetes Service (AKS).
• Expertise in Databricks (including Delta Lake, MLflow, and notebooks).
• Experience with ML model deployment, monitoring, and governance in a cloud-native environment.
• Experience with Feature Engineering
• Proficient in Python and familiar with libraries like scikit-learn, pandas, and TensorFlow or PyTorch.
• Experience with CI/CD pipelines (e.g., GitHub Actions, Azure DevOps, Jenkins).
• Familiarity with infrastructure as code (e.g., Terraform, ARM templates).
• Strong Communication skills / Stakeholder management skills, someone who can face off with business stakeholders on the data science side

Preferred Qualifications:

• Databricks Certified Professional or Microsoft Azure Certification.
• Experience with containerization (Kubernetes) and orchestration tools.
• Understanding of responsible AI principles and model explainability tools.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Contract

Job function

• Job function

  Engineering and Information Technology

• Industries

  Technology, Information and Media, Banking, and Financial Services

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