Delivery Consultant – Machine Learning Engineer, Data and Machine Learning, WWPS US Federal

Amazon; Arlington (VA); On-site; USD 90,000 - 150,000; Full time

Job summary

An established industry player is seeking a skilled Delivery Consultant specializing in Machine Learning Engineering. In this pivotal role, you will collaborate with clients to design and implement tailored AWS solutions, ensuring their technical requirements are met. Your expertise in cloud architecture and machine learning will drive customer success as you lead projects from inception to completion. This position offers a dynamic environment where innovation thrives, and your contributions will directly impact the cloud journey of various organizations. If you're passionate about technology and eager to make a difference, this opportunity is perfect for you.

Qualifications

• 3+ years in cloud architecture and implementation required.
• Experience in developing and deploying machine learning models.

Responsibilities

• Design and implement scalable AWS solutions tailored to customer needs.
• Provide technical guidance and support throughout project delivery.

Skills

Cloud Architecture

Software Development

Machine Learning

Deep Learning

Programming (Python)

Technical Guidance

Communication Skills

Education

Bachelor's degree in Computer Science

Graduate degree (MS or PhD)

Tools

AWS (EC2, S3, RDS, Lambda)

Terraform

PyTorch

TensorFlow

Job description

Delivery Consultant – Machine Learning Engineer, Data and Machine Learning, WWPS US Federal

Job ID: 2907586 | Amazon Web Services, Inc.

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.

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.

It is expected to work from one of the above locations (or customer sites) at least 1+ days in a week. This is not a remote position. You are expected to be in the office or with customers as needed.

This position requires that the candidate selected be a US Citizen and have the ability to obtain a Secret security clearance or higher.

Key job responsibilities
As an experienced technology professional, you will be responsible for:

1. Designing and implementing complex, scalable, and secure AWS solutions tailored to customer needs
2. Providing technical guidance and troubleshooting support throughout project delivery
3. Collaborating with stakeholders to gather requirements and propose effective migration strategies
4. Acting as a trusted advisor to customers on industry trends and emerging technologies
5. Sharing knowledge within the organization through mentoring, training, and creating reusable artifacts

BASIC QUALIFICATIONS

1. 3+ years of experience in cloud architecture and implementation
2. Bachelor's degree in Computer Science, Engineering, related field, or equivalent experience
3. 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
4. 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

PREFERRED QUALIFICATIONS

1. AWS experience preferred, with proficiency in a wide range of AWS services (e.g., EC2, S3, RDS, Lambda, IAM, VPC, CloudFormation)
2. AWS Professional level certifications (e.g., Solutions Architect Professional, DevOps Engineer Professional) preferred
3. Experience with automation and scripting (e.g., Terraform, Python)
4. Knowledge of security and compliance standards (e.g., HIPAA, GDPR)
5. Strong communication skills with the ability to explain technical concepts to both technical and non-technical audiences
6. 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.
7. 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.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.