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AI/ML Engineer, Professional Services

Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform, pioneering cloud computing and continuously innovating.
Seoul, South Korea
Machine Learning
Senior Software Engineer
Hybrid
5,000+ Employees
5+ years of experience
AI · Enterprise SaaS

Job Description

Are you looking to work at the forefront of Machine Learning and AI? AWS is seeking an experienced AI/ML Engineer to join our Professional Services team. In this role, you'll be at the cutting edge of AI technology, working with enterprise customers to implement state-of-the-art AI/ML solutions.

You'll be responsible for applying Generative AI algorithms to solve real-world problems with significant impact, working with massive amounts of data to develop Machine Learning (ML) and Deep Learning (DL) models. As part of AWS, you'll be joining a company that has been investing in Machine Learning for decades, pioneering and shaping the world's AI technology.

Your role will involve direct collaboration with customers, helping them understand and implement AI/ML solutions, delivering briefings and deep dive sessions, and guiding them on adoption patterns and paths to production. You'll work with AI/ML scientists, engineers, and architects to research, design, develop, and evaluate AI/ML algorithms addressing real-world challenges.

Key responsibilities include:

  • Establishing scalable, efficient, automated processes for large-scale data analyses
  • Creating and delivering best practice recommendations and technical content
  • Providing valuable feedback to Product and Engineering teams
  • Implementing and fine-tuning Large Language Models
  • Building and optimizing machine learning pipelines

The ideal candidate will have significant experience with Large Language Models (LLMs) and Prompt Engineering, strong Python skills, and hands-on experience with deep learning frameworks. You should be comfortable with machine learning libraries and have strong data engineering and communication skills.

This is a customer-facing role that may require travel to client locations. You'll be part of AWS Global Services, working alongside experts who help customers design, build, operate, and secure their cloud environments. Join our diverse team of technical experts who are helping customers achieve more with the AWS cloud.

AWS values diverse experiences and perspectives. We encourage applications from candidates with non-traditional career paths or alternative experiences. We offer excellent benefits, including work-life harmony, mentorship opportunities, and continuous learning resources to help you grow professionally.

Join us in shaping the future of AI and machine learning while working with some of the world's most innovative companies.

Last updated 25 days ago

Responsibilities For AI/ML Engineer, Professional Services

  • Collaborate with AI/ML scientists, engineers, and architects to research, design, develop, and evaluate AI/ML algorithms
  • Interact with customers directly to understand business problems and implement AI/ML solutions
  • Establish scalable, efficient, automated processes for large scale data analyses and model development
  • Create and deliver best practice recommendations, tutorials, blog posts, and presentations
  • Provide customer and market feedback to Product and Engineering teams

Requirements For AI/ML Engineer, Professional Services

Python
  • Significant years of industry experience building models for business applications
  • Experience with Large Language Models (LLMs) and Prompt Engineering
  • Experience in algorithms, data structures, numerical optimization, data mining, parallel computing
  • Experience in Python and hands-on experience with deep learning frameworks
  • Experience using machine learning libraries like scikit-learn, NumPy, Pandas, MLlib
  • Strong data engineering skills and communication skills

Benefits For AI/ML Engineer, Professional Services

Medical Insurance
Dental Insurance
Vision Insurance
  • Work-life balance
  • Flexible working culture
  • Mentorship opportunities
  • Career development resources
  • Knowledge-sharing environment