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

S.I. Systems Ltd.; Toronto; In loco; CAD 140.000 - 190.000; Tempo pieno

Descrizione del lavoro

S.I. Systems Ltd. in Toronto seeks a Senior Machine Learning Engineer to lead the development of next-generation personalization systems, including their Multimodal Recommendation Engine and emerging GenAI initiatives.

You will work with massive-scale datasets across the retail ecosystem to build sophisticated personalization experiences that impact millions of Canadians daily, focusing on scalable AI/ML pipelines and cloud infrastructure on Google Cloud Platform.

Competenze

• 5+ years of experience in Machine Learning engineering

Mansioni

• 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 scalable, robust cloud infrastructure on Google Cloud Platform 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 needs and build solutions that improve platform usability, scalability, and development experience.
• Optimize data processing pipelines and cloud resources for 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 ML.

Conoscenze

GenAI applications

Python

SQL

Docker

Kubernetes

GCP

Vertex AI

Formazione

Master's or PhD in Computer Science or ML

Strumenti

LangChain

LangGraph

Airflow/Cloud Composer

Vertex AI

BigQuery

BigTable

AlloyDB

Cloud Composer

Descrizione del lavoro

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 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.

Disclaimer:
AI may be used in evaluating candidates.
This posting is for an existing vacancy.