Machine Learning Engineer , Amazon Customer Service
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Key skills for this role
About the Role
Amazon Customer Service is looking for a Machine Learning Engineer to design and build robust, scalable AI/ML systems and infrastructure. You will architect end-to-end AI pipelines, develop generative AI solutions including LLMs and intelligent agents, and build infrastructure supporting the complete model lifecycle.
Key Skills for This Role
Responsibilities
- Design and implement enterprise scale AI/ML pipelines and model serving infrastructure
- Architect and build AI platform infrastructure supporting the complete model lifecycle
- Develop and deploy generative AI solutions including LLM based applications, RAG systems, AI agents, and intelligent automation workflows
- Build and optimize AI model serving systems for production use
- Develop and maintain robust AI governance frameworks
- Drive technical architecture decisions and system design for distributed AI/ML services
- Own end to end delivery of AI/ML solutions
- Collaborate with cross functional teams including Product Managers, Applied Scientists, and Data Engineers
Requirements
- 3+ years of contributing to new and current systems architecture and design experience
- Experience with Machine Learning and Large Language Model fundamentals
- Experience in machine learning, data mining, information retrieval, statistics or natural language processing
- 3+ years of full software development life cycle 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
Full Job Posting
Description
- We are looking for a Machine Learning Engineer on the Data Intelligence team within Amazon Customer Service.
- You will design and build robust, scalable AI/ML systems and infrastructure, architect end to end AI pipelines, and develop production grade AI services including generative AI, LLMs, and intelligent agent systems.
Key job responsibilities
- Design and implement enterprise scale AI/ML pipelines and model serving infrastructure
- Architect and build AI platform infrastructure supporting the complete model lifecycle
- Develop and deploy generative AI solutions including LLM based applications, RAG systems, AI agents, and intelligent automation workflows
- Build and optimize AI model serving systems for production use
- Develop and maintain robust AI governance frameworks
- Drive technical architecture decisions and system design for distributed AI/ML services
- Own end to end delivery of AI/ML solutions
- Collaborate with cross functional teams
A day in the life
- Review model performance metrics and experiment results
- Collaborate with Applied Scientists to optimize LLM prompting strategies or model architectures
- Write and review code for AI/ML pipelines, generative AI applications, and model serving systems
- Monitor and optimize existing AI services for performance, accuracy, and reliability
- Mentor junior engineers
About the team
- The Data Intelligence team owns the end to end process of defining, building, implementing, and monitoring a comprehensive data and AI strategy.
- We develop and apply GenAI, LLMs, Computer Vision, ML, Knowledge Graphs, and NLP to customer service associate experiences.
Basic Qualifications
- 3+ years of contributing to new and current systems architecture and design experience
- Experience with Machine Learning and Large Language Model fundamentals
- Experience in machine learning, data mining, information retrieval, statistics or natural language processing
Preferred Qualifications
- 3+ years of full software development life cycle 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
Salary
- Base salary range: CAN, BC, Vancouver 114,800.00 191,800.00 CAD annually
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