Deep Learning Architect, Gen AI Innovation Center
3 weeks ago
The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and fine tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently.
You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.
We’re looking for top architects, system and software engineers capable of using ML, Generative AI and other techniques to design, evangelize, implement and fine tune state-of-the-art solutions for never-before-solved problems.
This position requires that the candidate selected be a US Citizen.
Key job responsibilities
- Use ML and Generative AI tools, such as Amazon SageMaker and Amazon Bedrock, to provide a scalable cloud environment for our customers to label data, build, train, tune and deploy their models
- Collaborate with our data scientists to create and fine tune scalable ML, provide data labeling support and evaluate workflows for Generative AI solutions
- 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
- Ensure the system is scalable and capable of handling large datasets and high-demand workloads to support Gen AI initiatives
A day in the life
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
About the team
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
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
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Sales, Marketing and Global Services (SMGS)
AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.
We are open to hiring candidates to work out of one of the following locations:
Arlington, VA, USA | Denver, CO, USA
BASIC QUALIFICATIONS
- Bachelor of Science degree in Computer Science, or related technical, math or scientific field (or equivalent experience)- Experience coding in Python, R, Matlab, Java, or other modern programming language
- 1+ year of public cloud computer experience in AWS or other large scale cloud providers
- 1+ year of experience hosting and deploying ML solutions (e.g. for training, fine tuning, and inferences)
PREFERRED QUALIFICATIONS
- Masters or 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
- Hands on experience with deep learning (e.g., CNN, RNN, LSTM, Transformer), machine learning, CV, GNN, or distributed training
- Strong communication skills, with attention to detail and ability to convey rigorous mathematical concepts and considerations to non-experts
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