Machine Learning Engineer, Workforce Solutions - Analytics and Tech

$129,300 - $223,600/Yr

Amazon - Tempe, AZ

Full-time - Mid Level

Tempe, AZ

Sporting Goods, Hobby, Musical Instrument, Book, and Miscellaneous Retailers

About the position

The Machine Learning Engineer for Workforce Solutions at Amazon is responsible for designing and developing scalable AI and ML systems that address staffing challenges within Amazon's warehouses. This role involves working with cutting-edge technologies and collaborating with scientists to implement ML-powered products that have a significant impact on over a million Amazon associates. The engineer will engage in various initiatives, including developing personalized recommendation systems and AI Assistant tools, while ensuring high-quality architecture and design of AI/ML systems.

Responsibilities

• Design, implement, and productionize AI/ML models in collaboration with scientists.
• Develop ML/LLM workflows and end-to-end pipelines for data preparation, training, deployment, and monitoring.
• Leverage AWS AI services and other tools to accelerate AI investments.
• Understand complex application data flows and bridge the gap between technical and business requirements.
• Identify state-of-the-art models to enable new capabilities and increase operational efficiency.
• Share expert knowledge in performance, scalability, and engineering best practices.
• Provide thought leadership in selecting, defining, training, and fine-tuning Large Language Models (LLMs).
• Mentor other engineers on AI/ML initiatives and foster a culture of learning.
• Define data and feature validation strategies.
• Deploy models to production systems and operate them, including monitoring and troubleshooting.

Requirements

• 3+ years of non-internship professional software development experience.
• 2+ years of experience in design or architecture of new and existing systems.
• Experience programming with at least one software programming language.

Nice-to-haves

• 3+ years of full software development life cycle experience, including coding standards and operations experience.
• Bachelor's degree in computer science or equivalent.

Benefits

• Medical insurance
• Financial benefits
• Equity options
• Sign-on payments
• Comprehensive employee benefits package