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
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