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About the Role

The Amazon Web Services Professional Services (ProServe) team is seeking a skilled ML Engineer to join our team as a Delivery Consultant. In this role, you'll work closely with customers to design, implement, and manage AWS AI/ML and GenAI solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer success through their cloud journey, providing technical expertise and best practices throughout the ML project lifecycle.

Responsibilities

Implement end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, deployment and monitoring
Design and implement machine learning pipelines that support high-performance, reliable, scalable, and secure ML workloads
Design scalable ML solutions and operations (MLOps) using AWS services and leveraging GenAI solutions when applicable
Collaborate with cross-functional teams (Applied Science, DevOps, Data Engineering, Cloud Infrastructure, Applications) to prepare, analyze, and operationalize data and AI/ML models
Serve as a trusted advisor to customers on AI/ML and GenAI solutions and cloud architectures
Share knowledge and best practices within the organization through mentoring, training, publication, and creating reusable artifacts
Ensure solutions meet industry standards and support customers in advancing their AI/ML, GenAI, and cloud adoption strategies

Requirements

3+ years of software development, or 3+ years of scripting language experience
3+ years of building machine learning and generative AI models for business application experience
Experience with cloud services related to machine learning (e.g., Amazon SageMaker) and generative AI applications
Knowledge of AWS services including compute, storage, networking, security, databases, machine learning, and serverless technologies
Knowledge of AWS services including SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch and AWS certifications
2+ years of experience with design, deployment, and evaluation of AI agents and orchestration approaches; experience with open source frameworks like LangChain, LangGraph, LlamaIndex, and/or similar tools
3+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience using PyTorch or TensorFlow
Experience building ML pipelines with MLOps best practices, including: data preprocessing, distributed & GPU training, model deployment, monitoring, and retraining; experience with container and CI/CD pipelines
Domain expertise in healthcare and life sciences

Skills

Machine Learning
Artificial Intelligence
Generative AI
AWS
SageMaker
Bedrock
EC2
ECS
EKS
OpenSearch
PyTorch
TensorFlow
MLOps
LangChain
LangGraph
LlamaIndex

Location

USA, CA, San Francisco
USA, CO, Denver
USA, GA, Atlanta
USA, IL, Chicago
USA, NJ, Jersey City
USA, NY, New York
USA, TX, Dallas
USA, VA, Arlington
USA, VA, Herndon
USA, WA, Seattle

Work Type

Customer-facing role
Potential travel to customer sites as needed

Experience Level

3+ years of software development
3+ years of scripting language experience
3+ years of building machine learning and generative AI models for business application experience
2+ years of experience with design, deployment, and evaluation of AI agents and orchestration approaches
3+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience

Salary/Compensations

San Francisco: $151,000.00 - $204,300.00 USD annually
Denver: $131,300.00 - $177,600.00 USD annually
Atlanta: $131,300.00 - $177,600.00 USD annually
Chicago: $131,300.00 - $177,600.00 USD annually
Jersey City: $144,500.00 - $195,400.00 USD annually
New York: $144,500.00 - $195,400.00 USD annually
Dallas: $131,300.00 - $177,600.00 USD annually
Arlington: $131,300.00 - $177,600.00 USD annually
Herndon: $131,300.00 - $177,600.00 USD annually
Seattle: $131,300.00 - $177,600.00 USD annually

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

About the Company

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform.
We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Our inclusive culture empowers Amazonians to deliver the best results for our customers.

Equal Opportunity

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information.