Senior Machine Learning Engineer to lead the development of theirnext-generation personalization systems

Senior Machine Learning Engineer to lead the development of their next-generation personalization systems

Our Client is Canada's largest retailer. They are looking for a Senior Machine Learning Engineer to lead the development of their next-generation personalization systems, including their Multimodal Recommendation Engine and emerging generative AI initiatives .

You’ll work with massive-scale datasets across our retail ecosystem to build sophisticated personalization experience that impact millions of Canadians daily.

Duration: 6 months (to start)

Responsibilities:

• Lead the development and optimization of generative AI applications for personalized product discovery, search enhancement, and customer engagement.
• Leverage cutting-edge GenAI techniques, prompt engineering, and transformer architectures, owning end-to-end development of scalable AI/ML pipelines.
• Design, build, and maintain highly scalable, robust, and efficient cloud infrastructure using Google Cloud Platform (GCP) services, including Vertex AI, BigTable, BigQuery, AlloyDB, and Cloud Composer.
• Develop automation and orchestration of ML pipelines, integrating data ingestion, feature engineering, training, and deployment processes.
• Collaborate with cross-functional teams to understand their needs and build solutions that improve platform usability, scalability, and the overall development experience.
• Optimize data processing pipelines and cloud resources to ensure low-latency, cost-effective operation.
• Implement monitoring, alerting, and failover strategies to ensure platform reliability.
• Stay current with industry trends and best practices in cloud engineering, data engineering, and machine learning.

Must Haves:

• 5+ years of experience in Machine Learning engineering , with a focus on GenAI applications for personalization.
• Strong expertise in GenAI frameworks (LangChain or LangGraph) and building production-grade ML systems.
• Proven experience with GCP services (Airflow/Cloud Composer + Vertex AI) and ML infrastructure at scale.
• Proficiency in Python, SQL , and cloud-native development.
• Experience with containerization (Docker) and orchestration (Kubernetes) .
• Track record of deploying ML models to production at scale.
• Master's or PhD in Computer Science, Machine Learning, or a related field.

Nice to Haves:

• Experience with multimodal deep learning architectures and generative AI models.
• Knowledge of modern recommendation system architectures (transformers, neural collaborative filtering).
• Expertise in building real-time inference systems.
• Experience with distributed computing frameworks (Spark) and big data processing.

Our Client is Canada's largest retailer. They are looking for a Senior Machine Learning Engineer to lead the development of their next-generation personalization systems, including their Multimodal Recommendation Engine and emerging generative AI initiatives .

You’ll work with massive-scale datasets across our retail ecosystem to build sophisticated personalization experience that impact millions of Canadians daily.

Location: Toronto (1 day/week onsite)

Duration: 6 months (to start)

Responsibilities:

• Lead the development and optimization of generative AI applications for personalized product discovery, search enhancement, and customer engagement.
• Leverage cutting-edge GenAI techniques, prompt engineering, and transformer architectures, owning end-to-end development of scalable AI/ML pipelines.
• Design, build, and maintain highly scalable, robust, and efficient cloud infrastructure using Google Cloud Platform (GCP) services, including Vertex AI, BigTable, BigQuery, AlloyDB, and Cloud Composer.
• Develop automation and orchestration of ML pipelines, integrating data ingestion, feature engineering, training, and deployment processes.
• Collaborate with cross-functional teams to understand their needs and