AI Engineer

We are 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.
In this role, you will design, develop, and deploy AI-driven solutions that leverage data science, predictive modeling, and generative AI to solve complex business challenges.

AI Engineer
at Stacktics Inc. will be a key member of the 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 organization'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.

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.

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.

WHAT'S IN IT FOR YOU?

• 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
• Fun Employee Events and Activities
• Participation in Community Engagement
• Quarterly CEO coffee breaks