AI Engineer (Google Cloud)

Stacktics Inc.; Toronto; Remote; CAD 90,000 - 120,000; Full time

Job summary

A data analytics firm in Toronto is seeking a skilled AI Engineer to develop AI-driven solutions for complex business challenges. The role requires expertise in GCP, machine learning, and analytics. The ideal candidate will have a minimum of 4 years of experience and a strong ability in Python and SQL. This position offers a flexible working policy and a comprehensive benefits package.

Benefits

Flexible Remote Working Policy

100% employer-paid benefits package

Regular Lunch and Learns

Standing desks

Fully-loaded kitchen

Awesome Employee Events

Qualifications

• Experience with deploying AI/ML models on GCP.
• Hands-on experience with CI/CD pipelines.
• Proficiency in designing scalable data pipelines.

Responsibilities

• Define technical direction for AI/ML initiatives.
• Integrate AI solutions with enterprise-scale data pipelines.
• Lead implementation of marketing analytics stack.

Skills

Machine Learning

Data Analytics

Python

SQL

Bayesian Modeling

Cloud Platforms

Education

4+ years of experience in AI/ML

Google Cloud certifications

Tools

Google Cloud Platform

BigQuery

Cloud Storage

Job description

Overview

Stacktics Inc is seeking a highly skilled and hands-on AI Engineer with proven experience in deploying AI/ML models on Google Cloud Platform (GCP), particularly using Vertex AI. The successful candidate will design, develop, and deploy AI-driven solutions that leverage data science, predictive modeling, and generative AI to solve complex business challenges.

The AI Engineer will be a key member of the Stacktics Data Analytics team, responsible for driving high-quality, efficient service and data analytics delivery. This role will focus on advancing and maintaining industry-leading standards while expanding the company’s advanced analytics workflows and capabilities to support growth and innovation.

Key Responsibilities

• AI/ML solution design: define technical direction, architecture, and strategy for AI/ML initiatives, ensuring alignment with business objectives.
• Apply Bayesian modeling techniques to develop probabilistic models for prediction, classification, and decision-making under uncertainty.
• Leverage data analytics to extract insights, define KPIs, and guide model development using statistical and machine learning approaches.
• Develop and fine-tune transformer-based and generative AI models, applying prompt engineering, vector-based retrieval, and embedding techniques for improved accuracy.
• Prototype and evaluate AI solutions using proofs of concept and pilot projects to validate impact before full deployment.
• Design experiments to measure model efficacy, balancing accuracy, interpretability, and computational cost.
• Integrate AI solutions with enterprise-scale data pipelines, ensuring scalability, reliability, and compliance.
• Research emerging AI/ML technologies and contribute to build-vs-buy decisions for tools, frameworks, and cloud services.
• Collaborate cross-functionally with data scientists and data engineers to ensure seamless delivery of AI-powered features.
• Develop and maintain scalable data pipelines and ETL processes in collaboration with engineering teams.
• Create and maintain dashboards and data visualizations to support business decision-making using tools such as Looker.
• Lead the implementation and management of our marketing analytics stack, including Google Tag Manager (GTM) and Google Analytics 4 (GA4).
• Identify patterns from historical data, generate and test hypotheses, and provide product owners with actionable insights.
• Design testing processes, create and execute test cases for advanced analytical workflows.
• Troubleshoot and resolve issues and defects.

Company-Wide Responsibilities

• Maintain and exceed client satisfaction with Stacktics’ deliverables, day-to-day work, and overall value as a partner.
• Cultivate opportunities for company growth and seek areas where Stacktics’ role could be expanded.
• Adapt to ever-changing client needs and expectations.
• Maintain dedication toward achieving excellence in delivering client solutions and overall organizational success.
• Be an enthusiastic, positive, and collaborative teammate and mentor who is always eager to learn.
• Stay up-to-date on relevant technologies, engage with user groups, and understand trends to ensure we are using the best possible techniques and tools.

Preferred Qualifications

Candidates with the following qualifications will be given preference:

• Hands-on experience with GCP’s MLOps stack, including CI/CD pipelines, Vertex AI, BigQuery, and Cloud Storage.
• Strong knowledge of time-series forecasting, causal inference, or incrementality measurement.
• Relevant Google Cloud certifications such as Professional Machine Learning Engineer or Professional Data Engineer.

Qualifications

• 4+ years of experience in AI/ML, data analytics, with a proven track record of driving measurable impact.
• 3+ years of hands-on experience with Bayesian modeling and probabilistic inference techniques.
• Proficiency in Python and experience integrating AI models with cloud AI platforms ( Google Vertex AI)
• 3+ years of experience using SQL, with a strong ability to write large, dynamic analytical queries.
• Experience with solution architecture design and cloud-native ML system deployment.
• Ability to design and automate CI/CD pipelines for ML using Vertex AI Pipelines, Cloud Build, or similar tools.
• Exposure to generative AI applications for data-driven insights and automation.
• Understanding of responsible AI principles and bias mitigation techniques.
• Experience working on a cloud platform (GCP preferred).
• Deep understanding of Google Marketing Platform (GTM, GA4, GA360) and their implementation is a strong asset.

Benefits

• Flexible Remote Working Policy (within Canada)
• 100% employer-paid benefits package
• Regular Lunch and Learns from your Team Mates
• Standing desks
• Fully-loaded kitchen: snacks/fruit/drinks
• Awesome Employee Events and Activities
• Participation in Community Engagement