Delivery Consultant - GenAI/ML & Data Science @ Amazon Web Services (AWS)
Your Application Journey
Email Hiring Manager
Job Details
Overview
The Delivery Consultant - GenAI/ML & Data Science at Amazon Web Services (AWS) works closely with customers to design, implement, and manage AWS solutions that align with technical requirements and business objectives. This role involves architecting scalable, secure, and complex GenAI and ML applications, and guiding customers through their cloud journey.
Key Responsibilities
- Design and implement AWS-based GenAI and ML applications.
- Provide technical guidance and support throughout project lifecycles.
- Collaborate with customer stakeholders to gather requirements and propose migration strategies.
- Mentor team members and share best practices internally.
About the Team
AWS Professional Services is a global team that helps customers achieve business outcomes using the AWS Cloud. The team collaborates with stakeholders and partners to execute enterprise cloud initiatives and provides focused guidance through various specialty practices.
Qualifications
- 5+ years in cloud solution architecture and GenAI/ML solution deployment.
- Strong coding skills in Java, Python, SQL, and scripting languages.
- PhD or Masters in Computer Science or a related field, or equivalent experience.
- Deep understanding of AWS products (e.g., SageMaker, Bedrock, EMR, Lambda, EC2).
- Experience with deep learning frameworks and cloud migration strategies.
Benefits & Culture
AWS offers a diverse, inclusive culture with mentorship, career growth opportunities, and work/life balance. Learn and grow with a team that values individual differences and encourages continuous improvement.
Key skills/competency
- AWS
- GenAI
- Machine Learning
- Cloud Architecture
- Data Science
- Python
- Deep Learning
- Migration
- Consulting
- Solution Delivery
How to Get Hired at Amazon Web Services (AWS)
🎯 Tips for Getting Hired
- Customize your resume: Tailor details to AWS solutions and cloud experience.
- Highlight technical skills: Emphasize expertise in AWS, Python, and ML frameworks.
- Research AWS culture: Review their mission, values, and recent projects.
- Prepare detailed examples: Showcase past AWS project successes.