AI Engineer (GCP) at Stacktics
Toronto, ON, Canada -
Full Time


Start Date

Immediate

Expiry Date

09 Nov, 25

Salary

0.0

Posted On

09 Aug, 25

Experience

3 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Sql, Cloud Storage, System Deployment, Python, Data Analytics, Automation, Causal Inference, Ml

Industry

Information Technology/IT

Description

Toronto
Work Type: Full Time
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.

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.

How To Apply:

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Responsibilities

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.
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