Machine Learning Engineer, Data and Machine Learning, WWPS US Federal

$118,200 - $204,300/Yr

Amazon - Annapolis, MD

Full-time - Mid Level

Onsite - Annapolis, MD

5,001-10,000 employees

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

About the position

The Machine Learning Engineer position at AWS ProServe focuses on applying advanced machine learning and AI techniques, particularly in natural language processing (NLP) and generative AI, to assist U.S. Federal agencies in implementing innovative cloud solutions. The role involves collaborating with customers to understand their data challenges and designing tailored solutions, while also delivering proof-of-concept projects and leading implementation efforts.

Responsibilities

• Interact with customers directly to understand their business problems and help them define and implement scalable ML/DL solutions.
• Work closely with account teams, research scientist teams, and product engineering teams to drive model implementations and new algorithms.
• Design and run experiments, research new algorithms, and optimize risk, profitability, and customer experience.
• Develop and deploy advanced ML models to solve diverse challenges and opportunities.

Requirements

• 3+ years of non-internship professional software development experience.
• 2+ years of non-internship design or architecture experience of new and existing systems.
• Experience programming with at least one software programming language.
• 2+ years of relevant experience in developing and deploying large scale machine learning or deep learning models into production.
• Experience using Python and frameworks such as Pytorch and TensorFlow.

Nice-to-haves

• Experience leading the design, development, and deployment of business software at scale.
• Graduate degree (MS or PhD) in computer science, engineering, mathematics or related technical/scientific field.
• Practical experience in solving complex problems in an applied environment.
• Experience with AWS services such as SageMaker, EMR, S3, DynamoDB, and EC2.

Benefits

• Flexible work hours and arrangements
• Mentorship and career growth opportunities
• Diversity and inclusion programs
• Work-life balance initiatives