Senior AI Engineer - AI Platform & ML Engineering

Aviso WealthToronto, ON
CA$135,000 - CA$150,000

About The Position

We’re looking for an AI Engineer, AI Platform & ML Engineering to join our Data & AI Technology Partners team. Reporting to the Sr. Director of Data Science and AI Enablement, the AI Platform & ML Engineering is responsible for focusing on the platform patterns, MLOps practices, model lifecycle, deployment standards, monitoring, evaluation, and governance integration needed to move AI and machine learning solutions beyond experimentation. This is a hands-on engineering role for someone who wants to build the foundation that allows AI solutions to become repeatable, governed, observable, and production ready.

Requirements

  • Bachelor’s or Master's Degree in Computer Science, Software Engineering, Data Engineering, Data Science, Artificial Intelligence, Machine Learning, Mathematics, Statistics, Engineering or related technical field
  • Equivalent hands-on experience building data, AI, machine learning, platform, or cloud engineering solutions may be considered in place of formal education
  • 10+ years of overall experience with 4+ years of experience building, deploying, or supporting machine learning, AI, or data-driven solutions in production environments and 5 to 7 years working in the data space
  • Databricks certification related to Machine Learning, Data Engineering, Generative AI or platform administration
  • AWS certifications related to cloud architecture, machine learning, AI, DevOps, data engineering or security
  • Microsoft Azure certifications related to AI, data, cloud engineering, DevOps, or security
  • Other relevant certifications in MLOps, LLMOps, cloud platforms, DevOps, security, architecture, or enterprise AI platforms
  • Strong Python development skills, especially for ML engineering, automation, APIs, testing and production implementation
  • Hands-on experience with cloud-based AI/ML platforms; experience with AWS an asset, Databricks, Azure, MLflow or Lakehouse platforms
  • Strong understanding of MLOps, CI/CD/CT, model deployment, model serving, and production release practices for AI and ML solutions
  • Experience with model evaluation, validation, monitoring and observability, including model performance, drift, reliability, latency, usage and cost
  • Familiarity with LLMOps practices that support GenAI and agentic solutions in production, including prompt/model versioning, evaluation pipelines, controlled releases, and production support patterns
  • Experience developing reusable AI/ML platform patterns, including deployment templates, secure serving patterns, feature engineering standards, and integration frameworks
  • Understanding of enterprise security, governance, and control requirements for production AI and ML workloads
  • Strong consultative and communication skills, with the ability to explain technical trade-offs to data, technology, risk, governance, and business stakeholders
  • Fluent communication skills in English are required

Nice To Haves

  • bilingual skills in French are an asset

Responsibilities

  • Build reusable AL and ML engineering patterns that help teams move from proof-of-value to production safely and consistently
  • Establish practical MLOps and LLMOps practices using Databricks, AWS, MLflow and related platform capabilities
  • Create standards and templates for model deployment, serving, monitoring, evaluation, and production release
  • Support API integration and deployment patterns for ML, GenAI and agentic solutions
  • Partner with Data Engineering & Data Management to define feature engineering data product, and reusable pipeline patterns for AI/ML use cases
  • Help define how models, prompts, agents, data products, and AI outputs are versioned, tracked, monitored, and governed
  • Partner with Data & AI Governance to embed responsible AI, lineage, access control, auditability, and risk controls into production workflows
  • Help monitor AI cost, performance, reliability, usage, and operational risk, while contributing to reusable standards and community learning

Benefits

  • Competitive compensation package that rewards and recognizes individual contributions
  • Excellent health, dental and insurance benefits to meet the diverse needs of our employees
  • Generous vacation time, fitness benefit, parental leave top-up options
  • Matching contributions to our retirement program
  • Commitment to the continuous improvement of our staff through learning & development and an education assistance program
  • Regular social events to foster teamwork
© 2026 Teal Labs, Inc
Privacy PolicyTerms of Service