stacktics
stacktics~1d ago
New

AI Engineer (Google Cloud)

Machine Learning EngineerData
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Quick Summary

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…

Key Responsibilities

AI/ML solution design: define technical direction, architecture, and strategy for AI/ML initiatives, ensuring alignment with business objectives.

Requirements Summary

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.

Technical Tools
bigquerygcpgoogle-analyticslookerpythonsqlci-cddata-analysisetlforecastingmachine-learning

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.

Responsibilities

~2 min read
  • 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.

Responsibilities

~1 min read
  • 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.

Requirements

~1 min read

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.

Requirements

~1 min read
  • 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.
  • 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

Location & Eligibility

Where is the job
Toronto, Canada
On-site at the office
Who can apply
CA

Listing Details

First seen
May 6, 2026
Last seen
May 8, 2026

Posting Health

Days active
0
Repost count
0
Trust Level
51%
Scored at
May 6, 2026

Signal breakdown

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stackticsAI Engineer (Google Cloud)