AI Engineer (Google Cloud)
Quick Summary
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…
AI/ML solution design: define technical direction, architecture, and strategy for AI/ML initiatives, ensuring alignment with business objectives.
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.
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 readCandidates 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
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
Please let stacktics know you found this job on Jobera.
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