Amazon Delivery Consultant – Machine Learning Engineer 

United States, Texas, Arlington 

875524349

The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Delivery Consultant to join our team at Amazon Web Services (AWS). In this role, you'll work closely with customers to design, implement, and manage AWS 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 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 solutions tailored to meet the specific needs of each customer. You’ll 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.This position requires that the candidate selected must currently possess and maintain an active TS/SCI Security Clearance with Polygraph. The position further requires the candidate to opt into a commensurate clearance for each government agency for which they perform AWS work.Key job responsibilities
As an experienced technology professional, you will be responsible for:- Providing technical guidance and troubleshooting support throughout project delivery
- Collaborating with stakeholders to gather requirements and propose effective migration strategies- Sharing knowledge within the organization through mentoring, training, and creating reusable artifactsDiverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Work/Life Balance
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

- 3+ years of experience in cloud architecture and implementation, [Alternative: Experience in cloud architecture and implementation
- Bachelor's degree in Computer Science, Engineering, related field, or equivalent experience
- 3+ years of non-internship professional experience in Software development, Designing and architecting new and existing systems (using design patterns, ensuring reliability and scaling), Programming with at least one software programming language
- 3+ years of relevant experience in developing and deploying large-scale machine learning or deep learning models/systems into production, batch and real-time data processing, model containerization, CI/CD pipelines, API development, model training and productionizing ML models, and using Python and frameworks such as PyTorch, TensorFlow
- Current, active US Government Security Clearance of TS/SCI with Polygraph

- AWS experience preferred, with proficiency in a wide range of AWS services (e.g., EC2, S3, RDS, Lambda, IAM, VPC, CloudFormation)
- AWS Professional level certifications (e.g., Solutions Architect Professional, DevOps Engineer Professional) preferred
- Experience with automation and scripting (e.g., Terraform, Python)
- Knowledge of security and compliance standards (e.g., HIPAA, GDPR)
- Strong communication skills with the ability to explain technical concepts to both technical and non-technical audiences
- Graduate degree (MS or PhD) in computer science, engineering, mathematics or a related technical/scientific field, with practical experience in solving complex problems in an applied environment.
- Proficiency in Python and frameworks such as PyTorch and TensorFlow, as well as experience with AWS services like SageMaker, EMR, S3, DynamoDB, and EC2 for machine learning, deep learning, NLP, GenAI, distributed training, and model hosting.