Senior Machine Learning Engineer

Pay: 60-70

Vacancy: New Vacancy (New Role)

We may use artificial intelligence tools to assist with the screening, assessment, or selection of potential applicants for this position.

JOB DESCRIPTION

nsight Global is supporting a large Canadian retail client that is redefining how customers shop through innovative eCommerce experiences. Their digital team builds and operates online experiences across grocery, beauty, pharmacy, loyalty, and apparel, supporting millions of customer interactions. The team is leveraging advanced machine learning, AI, and emerging technologies such as generative AI to transform product discovery and create more personalized shopping experiences. We are seeking a Senior Machine Learning Engineer to help lead the development of next-generation personalization capabilities, including a Multimodal Recommendation Engine and emerging generative AI initiatives. This individual will work with large-scale datasets across the retail ecosystem to build sophisticated personalization experiences. What You'll Do Lead the development and optimization of generative AI applications focused on personalized product discovery, search enhancement, and customer engagement. Leverage GenAI techniques, prompt engineering, and transformer architectures to build scalable, end-to-end AI/ML pipelines. Design and maintain scalable cloud infrastructure within Google Cloud Platform (GCP), leveraging technologies such as Vertex AI, BigTable, BigQuery, AlloyDB, and Cloud Composer. Build and automate ML pipelines across data ingestion, feature engineering, model training, and deployment. Partner with cross-functional teams to develop solutions that improve platform scalability, usability, and overall development experience. Optimize data processing pipelines and cloud resources to support low-latency, cost-effective ML applications.

REQUIRED SKILLS AND EXPERIENCE

Top must-haves 1. 5+ years of ML Engineering experience o Should have actually built and deployed ML systems into production, not just experimentation/data science. 2. Strong Generative AI experience o Production GenAI applications o LLMs / transformer architectures o Prompt engineering o LangChain or LangGraph 3. Recommendation systems / personalization o This is a major piece of the role. o Look for personalized recommendations, product discovery, ranking/search, neural collaborative filtering, transformers, or similar experience. o Retail/eCommerce personalization would be especially aligned. 4. Very strong GCP o Vertex AI is especially important. o Ideally also experience with BigQuery, BigTable, AlloyDB and Cloud Composer/Airflow. 5. End-to-end ML engineering They need someone who can own: o Data ingestion o Feature engineering o Model training o Deployment/inference o Monitoring o ML pipeline automation/orchestration 6. Python + SQL o Both should be strong and hands-on. 7. Production cloud/container experience o Docker o Kubernetes o CI/CD o Experience operating ML workloads at scale