Amazon Deep Learning Architect Generative AI Innovation 

United States, Texas, Arlington 

2690753

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.
Key job responsibilities
As a Deep Learning Architect you are responsible for:
- Designing complex, scalable, and secure AWS ML architectures specifically for model optimization workloads including fine-tuning, continued pretraining, and reinforcement learning- Interacting directly with customers to understand their business problems and model customization requirements, guiding them through implementation of optimization solutions and paths to production
- Architecting MLOps pipelines and infrastructure for distributed training, model evaluation, and deployment at scale using tools such as MLflow and SageMaker Pipelines
- Designing and implementing data curation and distributed training pipelines for LLMs
- Optimizing AI models for deployment, developing custom solutions for enhanced performance
- Implementing Infrastructure as Code (IaC) solutions using CDK and Terraform for ML training and inference architectures
- Sharing knowledge within the organization through mentoring, training, and creating reusable artifacts for model optimization practicesDiverse Experiences
Amazon 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.Why AWS
Work/Life BalanceMentorship and 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.AWS Global Services

- Bachelor of Science degree in Computer Science, or related technical, math, or scientific field (or equivalent experience)
- 3+ years of experience in designing, building, and/or operating cloud solutions in a production environment
- 2+ year experience hosting and deploying ML solutions (e.g., for training, fine tuning, and inference)
- 2+ years of hands on experience with Python to build, train, and evaluate models
- 2+ years of technical client engagement experience

- Masters or PhD degree in computer science, or related technical, math, or scientific field
- Strong working knowledge of deep learning, machine learning, generative AI, and statistics
- Experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker
- Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
- Experience building cloud solutions with AWS