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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.
Key job responsibilities
• Collaborate with our applied and data scientists to build robust and scalable Generative AI solutions for business problems
• Effectively use Foundation Models available on Amazon Bedrock and Amazon SageMaker to meet our customer's performance needs
• Work hands on to build scalable cloud environment for our customers to label data, build, train, tune and deploy their models
• Interact with customer directly to understand the business problem, help and aid them in implementation of their ML ecosystem
• Analyze and extract relevant information from large amounts of historical data to help automate and optimize key processes
• Work closely with account teams, applied/data scientist teams, and product engineering teams to drive model implementations and new algorithms
• Mentor and develop junior members on the teamA day in the life
About AWSDiverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred 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.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.Work/Life Balance
- Experience coding in Python, R, Matlab, Java or other modern programming language
- Experience hosting and deploying ML solutions (e.g., for training, fine tuning, and inferences)
- Basic understanding of deep learning (e.g., CNN, RNN, LSTM, Transformer), Large Language Models, Large Multimodal Models and other GenAI Models such as Stable Diffusion and their finetuning and distributed training strategies
- PhD degree in computer science, or related technical, math, or scientific field
- Strong working knowledge of deep learning, machine learning and statistics
- Experiences related to AWS services such as SageMaker, Bedrock, EMR, S3, OpenSearch Service, Step Functions, Lambda, and EC2 or other large scale cloud providers‘ services
- Experiences related to Large Language Models, Large Multimodal Models or other GenAI Models such as Stable Diffusion and their finetuning and distributed training strategies
- Strong communication skills, with attention to detail and ability to convey rigorous mathematical concepts and considerations to non-experts
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