Deep Learning Architect, AWS Gen AI Innovation Center

hace 4 semanas

Xico, México Amazon A tiempo completo
About the Role

We are seeking a highly skilled Deep Learning Architect to join our team at the AWS Gen AI Innovation Center. As a key member of our team, you will play a critical role in helping our customers implement Generative AI solutions and realize transformational business opportunities.

Key Responsibilities
  • Design and develop bespoke solutions that harness the power of Generative AI to solve real-world problems with significant impact.
  • Work directly with customers to understand their business needs and develop tailored solutions that meet their requirements.
  • Collaborate with cross-functional teams to scope, train, and fine-tune Generative AI models, and develop proof-of-concepts.
  • Provide guidance on best practices for applying Generative AI responsibly and cost-efficiently.
  • Design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.
Requirements
  • Bachelor of Science degree in Computer Science, or related technical, math, or scientific field (or equivalent experience).
  • At least 5 years of experience in designing, building, and/or operating large-scale enterprise IT systems in a production environment.
  • At least 3 years of public cloud computing experience in AWS or other large-scale cloud providers.
  • Relevant experience hosting and deploying ML solutions (e.g., for training, fine-tuning, and inference).
  • Experience coding in Python, R, Matlab, Java, or other modern programming languages.
  • Experience communicating across technical and non-technical audiences, including executive-level stakeholders or clients.
  • Ability to communicate in a business setting in English and Spanish.
Preferred Qualifications
  • 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.
  • Hands-on experience building models with deep learning frameworks like MXNet, Tensorflow, Caffe, Torch, Theano, or similar.
  • The motivation to achieve results in a fast-paced environment.

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