Senior Machine Learning Engineer

Job summary

Lead the development and optimization of generative AI and personalization solutions for product discovery, search, and customer engagement. Build and operate scalable end-to-end ML pipelines and GCP infrastructure, optimizing data processing and cloud resources for low-latency, cost-effective applications.

Job details

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

What you’ll do

Lead the development and optimization of generative AI and personalization solutions for product discovery, search, and customer engagement. Build and operate scalable end-to-end ML pipelines and GCP infrastructure, optimizing data processing and cloud resources for low-latency, cost-effective applications.

Requirements

Requires 5+ years of hands-on machine learning engineering experience building and deploying production systems, with strong generative AI, LLM, transformer, prompt engineering, and recommendation or personalization experience. Candidates should be proficient in Python, SQL, GCP—especially Vertex AI—and end-to-end ML operations, with production experience using containers, Kubernetes, and CI/CD.

Listed skills

• prompt engineering · Preferred
• Python · Preferred
• SQL · Preferred
• Docker · Preferred
• Kubernetes · Preferred
• CI/CD · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Machine Learning Engineering
• Generative AI
• Large Language Models
• Transformer Architectures
• Prompt Engineering
• LangChain
• LangGraph
• Recommendation Systems
• Personalization
• Google Cloud Platform
• Vertex AI
• Python
• SQL
• Docker
• Kubernetes
• CI/CD

Job areas

• Technology
• Software
• Data & Analytics
• Retail
• Engineering

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