Delivery Consultant- AI​/ML, Data & Machine Learning; DML

Machine Learning Engineer

The Amazon Web Services Professional Services (Pro Serve) team is seeking a skilled Machine Learning Engineer to join our team at Amazon Web Services (AWS). 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  will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.

This position requires that the candidate selected be a US Citizen and must currently possess and maintain an active TS/SCI security clearance.

Key job responsibilities include designing and implementing complex, scalable, and secure AI/ML solutions on AWS tailored to customer needs, developing and deploying machine learning models and generative AI applications that solve real-world business problems, collaborating with customer stakeholders to identify high-value AI/ML use cases, providing technical guidance on applying AI, machine learning, and generative AI responsibly and cost-efficiently, acting as a trusted advisor to customers on the latest advancements in AI/ML, and 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.