Machine Learning Engineer , Amazon Customer Service

Amazon • Vancouver, BC

2d • CA$114,800 - CA$191,800 • Onsite

About The Position

We are looking for a Machine Learning Engineer on the Data Intelligence team which is part of Amazon Customer Service (CS) team, you will design and build robust, scalable AI/ML systems and infrastructure. You'll architect end-to-end AI pipelines for model training, evaluation, and deployment, implement secure and efficient data processing solutions, and develop production-grade AI services including generative AI, large language models (LLMs), and intelligent agent systems. Additionally, you'll build infrastructure that supports the complete lifecycle of AI models - from experimentation and development to production deployment and monitoring.

You'll work with cross-functional teams (e.g., scientists, product managers, data engineers) to create enterprise-scale AI/ML systems that handle high-volume inference workloads, implement comprehensive model and AI governance frameworks, and build scalable AI-powered products that power critical business capabilities.

If you enjoy solving complex AI and machine learning challenges in high-scale environments, working in a collaborative and dynamic team, and want to make a lasting impact on Amazon Customer Service worldwide, this is your opportunity. Come join us on this exciting journey!

Requirements

• 3+ years of contributing to new and current systems architecture and design (architecture, design patterns, reliability and scaling) experience
• Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution
• Experience in machine learning, data mining, information retrieval, statistics or natural language processing

Nice To Haves

• 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
• Master's degree in computer science or equivalent
• Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware

Responsibilities

• Design and implement enterprise-scale AI/ML pipelines and model serving infrastructure that ensure optimal performance, reliability, and low-latency inference for both traditional ML models and generative AI systems.
• Architect and build AI platform infrastructure that supports the complete model lifecycle, from training environments, feature stores, and validation frameworks to production deployment, A/B testing, and monitoring systems.
• Develop and deploy generative AI solutions, including LLM-based applications, retrieval-augmented generation (RAG) systems, AI agents, and intelligent automation workflows.
• Build and optimize AI model serving systems for production use, including model compression, quantization, prompt engineering pipelines, and efficient serving strategies to meet latency and throughput requirements.
• Develop and maintain robust AI governance frameworks, implementing security controls, guardrails, responsible AI practices, and compliant data access patterns that protect sensitive information.
• Drive technical architecture decisions and system design, focusing on scalability, reliability, and performance of distributed AI/ML services while ensuring alignment with business requirements.
• Own end-to-end delivery of AI/ML solutions, including design, implementation, experimentation, and verification of components, using standard software engineering and AI/ML engineering methodologies and best practices.
• Collaborate with cross-functional teams, including Product Managers, Applied Scientists, and Data Engineers, to understand requirements, conduct design reviews, and ensure successful delivery of AI solutions while maintaining high development standards.

Benefits

• health insurance (medical, dental, vision, prescription, basic life & AD&D insurance)
• Registered Retirement Savings Plan (RRSP)
• Deferred Profit Sharing Plan (DPSP)
• paid time off
• other resources to improve health and well-being

What This Job Offers

• Job Type: Full-time
• Career Level: Senior