Machine Learning Engineer, Data & Machine Learning (DML)

Amazon • Herndon, VA

1d • $131,300 - $177,600 • Onsite

About The Position

The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Machine Learning Engineer to join their team at Amazon Web Services (AWS). This role is at the forefront of Machine Learning and AI, applying Generative AI algorithms to solve real-world problems with significant impact. The engineer will work directly with customers to design, evangelize, implement, and scale AI/ML solutions that meet technical requirements and business objectives, driving customer success through their AI transformation journey. As a Machine Learning Engineer within the AWS Professional Services organization, the individual will be proficient in architecting complex, scalable, and secure machine learning solutions tailored to meet specific customer needs. This includes helping customers scope use cases, select, train, and fine-tune models, and navigate technical or business challenges. The role involves assessing current data infrastructure, developing proof-of-concepts, proposing strategies for implementing AI and generative AI solutions at scale, and designing/running experiments to optimize risk, profitability, and customer experience. The AWS Professional Services organization is a global team of experts assisting customers in realizing desired business outcomes using the AWS Cloud, collaborating with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives and providing focused guidance through global specialty practices.

Requirements

• 3+ years of cloud architecture and solution implementation experience
• Knowledge of the primary aws services (ec2, elb, rds, route53 & s3)
• Experience implementing AWS services in a variety of distributed computing environments
• 3+ years of machine learning/statistical modeling data analysis tools and techniques
• Current, active US Government Security Clearance of Top Secret or above

Nice To Haves

• 5+ years of IT implementation experience
• degree in advanced technology, or AWS Professional level certification
• Knowledge of AWS services including compute, storage, networking, security, databases, machine learning, and serverless technologies
• Knowledge of security and compliance standards including HIPAA and GDPR
• Experience and technical expertise (design and implementation) in cloud computing technologies
• Experience leading the design, development and deployment of business software at scale or recent hands-on technology infrastructure, network, compute, storage, and virtualization experience
• Experience in performance optimization and cost management for cloud environments
• Experience presenting technical solutions to diverse audiences in pre-sales environments
• 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

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

Benefits

• sign-on payments
• restricted stock units (RSUs)
• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed