Senior Generative AI Engineer Job at Knowit Training, Dallas, TX

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  • Knowit Training
  • Dallas, TX

Job Description

Senior Generative AI Engineer will build and maintain APIs and SDKs to train, fine-tune and access AI models at scale. You will work as part of our Enterprise AI team and build systems that will enable our users to work with Large-Language Models (LLMs) and Foundation Models (FMs), using our public cloud infrastructure. You will work with a team of world-class AI engineers and researchers to design and implement key API products and services that enable real-time customer-facing applications. Examples of projects you will work on include:
  • Architect, build and deploy well-managed core APIs and SDKs to access LLMs and our proprietary FMs including training, fine-tuning and prompting tasks, including orchestration SDKs.
  • Design APIs for performance, real-time applications, scale, ease of use and governance automation.
  • Develop application-specific interfaces that leverage LLMs and FMs to continue to enhance the associate and customer experience.
  • Enable our users to build new GenAI capabilities.
  • Develop tools and processes to monitor API access patterns and operational health.
  • Design and implement AI safety and guardrails in the API layer working closely with researchers.
Basic Qualifications:
  • Bachelor’s degree in Computer Science, Computer Engineering or a technical field
  • At least 4 years of experience designing and building and deploying ML application platforms.
  • At least 4 years of experience programming with Python, Go, Scala, or Java
  • At least 1 year of experience building, scaling, and optimizing training or inferencing systems for deep neural networks
Preferred Qualifications:
  • Familiarity with building large-scale AI and ML products or platforms serving millions of users.
  • Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP.
  • Experience with Kubernetes and KubeFlow workloads is preferred.
  • Familiarity with the Model Development Lifecycle and MLOps preferred.
  • Experience architecting cloud systems for security, availability, performance, scalability, and cost.
  • Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines.
  • Experience at tech and product-driven companies/startups preferred.
  • Ability to iterate rapidly with researchers and engineers to improve a product experience while building the foundational capabilities.
  • Have experience with API security, observability, cloud access control and privacy best practices.

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