Amazon Web Services (AWS) · 7 hours ago
Sr. Machine Learning Engineer, WWPS ProServe Data and Machine Learning
Amazon Web Services, Inc. is seeking a skilled Machine Learning Engineer to join their Professional Services team. In this role, you'll design, implement, and scale AI/ML solutions tailored to customer needs while collaborating with stakeholders to drive customer success through their AI transformation journey.
Artificial Intelligence (AI)Cloud ComputingConsultingSoftwareInformation TechnologyAgentic AIDevOpsWeb Development
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
Qualification
Required
Bachelor's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
5+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
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
Current, active US Government Security clearance of TS/SCI with Polygraph
Preferred
Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
Experience applying quantitative analysis to solve business problems and making data-driven business decisions
Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience transforming legacy SIGINT/Cyber capabilities with machine learning approaches, and building models within SIGINT/Cyber operational constraints
Experience applying data science within Intelligence Community production chains
Experience with Python, SQL/NoSQL, and API development for building and deploying AI/ML solutions
Experience with Large Language Models (LLMs), prompt engineering, and generative AI frameworks
Benefits
Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
401(k) matching
Paid time off
Parental leave
Company
Amazon Web Services (AWS)
Launched in 2006, Amazon Web Services (AWS) began exposing key infrastructure services to businesses in the form of web services -- now widely known as cloud computing.
Funding
Current Stage
Late StageTotal Funding
unknownKey Investors
BIRD Foundation
2025-01-22Grant
Leadership Team
Recent News
2026-02-13
2026-02-13
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