Machine Learning Engineer, Data & Machine Learning (DML)

Machine Learning Engineer

This position requires that the candidate selected be a US Citizen and currently possess and maintain an active Top Secret security clearance. The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Machine Learning Engineer to join our team at Amazon Web Services (AWS). Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? In this role, you'll work directly with customers to design, evangelize, implement, and scale AI/ML solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer success through their AI transformation journey, providing deep expertise in machine learning, generative AI, and best practices throughout the project lifecycle. As a Machine Learning Engineer within the AWS Professional Services organization, you will be proficient in architecting complex, scalable, and secure machine learning solutions tailored to meet the specific needs of each customer. You'll help customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and fine tune the right models, and define paths to navigate technical or business challenges. Working closely with stakeholders, you'll assess current data infrastructure, develop proof-of-concepts, and propose effective strategies for implementing AI and generative AI solutions at scale. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.

Key job responsibilities:

• Designing and implementing complex, scalable, and secure AI/ML solutions on AWS tailored to customer needs, including selecting and fine-tuning appropriate models for specific use cases
• Developing and deploying machine learning models and generative AI applications that solve real-world business problems, conducting experiments and optimizing for performance at scale
• Collaborating with customer stakeholders to identify high-value AI/ML use cases, gather requirements, and propose effective strategies for implementing machine learning and generative AI solutions
• Providing technical guidance on applying AI, machine learning, and generative AI responsibly and cost-efficiently, troubleshooting throughout project delivery and ensuring adherence to best practices
• Acting as a trusted advisor to customers on the latest advancements in AI/ML, emerging technologies, and innovative approaches to leveraging diverse data sources for maximum business impact
• Sharing knowledge within the organization through mentoring, training, creating reusable AI/ML artifacts, and working with team members to prototype new technologies and evaluate technical feasibility

About the team:

Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.

Basic Qualifications:

• Bachelor's degree or above in Science, Technology, Engineering, or Mathematics (STEM)
• Experience in professional software engineering & best practices for the full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
• 3+ years of machine learning/statistical modeling data analysis tools and techniques
• Current, active US Government Security Clearance of Top Secret or above

Preferred Qualifications:

• Master's degree or above in Science, Technology, Engineering, or Mathematics (STEM)
• Experience working on multi-team, cross-disciplinary projects
• Experience applying quantitative analysis to solve business problems and making data-driven business decisions
• Experience in defining and creating benchmarks for assessing GenAI model performance
• Experience with Python, SQL/NoSQL, and API development for building and deploying AI/ML solutions
• Experience working with Large Language Models (LLMs), prompt engineering, and generative AI frameworks