Delivery Consultant - Machine Learning Engineer, AWS Professional Services, AWS Professional Services

Are you excited about building software solutions around large complex Machine Learning (ML) and Artificial Intelligence (AI) systems Want to help the largest global enterprises derive business value through the adoption and automation of Generative AI (GenAI) Excited by using massive amounts of disparate data to develop AI/ML models Eager to learn to apply AI/ML to a diverse array of enterprise use Thrilled to be a key part of Amazon who has been investing in Machine Learning for decades - pioneering and shaping the worlds AI technology

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

Possessing a deep understanding of AWS products and services as a Delivery Consultant you will be proficient in architecting complex scalable and secure AI/ML and GenAI solutions tailored to meet the specific needs of each customer. Youll work closely with stakeholders to gather requirements assess current infrastructure and propose effective migration strategies to AWS. As trusted advisors to our customers providing guidance on industry trends emerging technologies and innovative solutions you will be responsible for leading the implementation process ensuring adherence to best practices optimizing performance and managing risks throughout the project.

The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices which cover a variety of solutions technologies and industries.

Key job responsibilities
Key job responsibilities
As an experienced technology professional you will be responsible for:
1. Implementing end-to-end AI/ML and GenAI projects from understanding business needs to data preparation model development deployment and monitoring.
2. Designing and implementing machine learning pipelines that support high-performance reliable scalable and secure ML workloads.
3. Designing scalable ML solutions and operations (MLOps) using AWS services and leveraging GenAI solutions when applicable.
4. Collaborating with cross-functional teams (Applied Science DevOps Data Engineering Cloud Infrastructure Applications) to prepare analyze and operationalize data and AI/ML models.
5. Serving as a trusted advisor to customers on AI/ML and GenAI solutions and cloud architectures
6. Sharing knowledge and best practices within the organization through mentoring training publication and creating reusable artifacts.
7. Ensuring solutions meet industry standards and supporting customers in advancing their AI/ML GenAI and cloud adoption strategies.

This is a customer-facing role with potential travel to customer sites as needed.

About the team
About AWS:
Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job below we encourage candidates to apply. If your career is just starting hasnt followed a traditional path or includes alternative experiences dont let it stop you from applying.
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Work/Life Balance - We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home theres nothing we cant achieve in the cloud.


- 3 years cloud architecture and implementation
- Bachelors degree in Computer Science Engineering related field or equivalent experience
- 5 years data software or ML engineering with strong understanding of distributed computing. (e.g. data pipelines training and inference ML infrastructure design)
- 3 years developing predictive modeling natural language processing and deep learning with a proven track record of building and deploying ML models on cloud. (e.g. Amazon SageMaker or similar)
- 3 years developing with SQL Python and at least one additional programming language (e.g. Java Scala JavaScript TypeScript). Proficient with leading ML libraries and frameworks (e.g. TensorFlow PyTorch)

- AWS experience preferred with proficiency in a range of AWS services (e.g. SageMaker Bedrock EC2 ECS EKS OpenSearch Step Functions VPC CloudFormation)
- AWS Professional certifications (e.g. Solutions Architect Professional DevOps Engineer Professional)
- Experience with automation (e.g. Terraform Python) Infrastructure as Code (e.g. CloudFormation CDK) and Containers & CI/CD Pipelines.
- Knowledge of common security and compliance standards (e.g. HIPAA GDPR)
- Strong communication skills with ability to explain complex concepts to technical and non-technical audiences
- Experience building ML pipelines with MLOps best practices including: data preprocessing model hosting feature selection hyperparameter tuning distributed & GPU training deployment monitoring and retraining
- Experience with MLOps (e.g. MLFlow Kubeflow) and orchestration (e.g. Airflow AWS Step Functions). Experience building applications using GenAI technologies (LLMs Vector Stores LangChain Prompt Engineering)

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. 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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $118200/year in our lowest geographic market up to $204300/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge skills and experience. Amazon is a total compensation company. Dependent on the position offered equity sign-on payments and other forms of compensation may be provided as part of a total compensation package in addition to a full range of medical financial and/or other benefits. For more information please visit This position will remain posted until filled. Applicants should apply via our internal or external career site.