Senior Generative AI Engineer, Enterprise Platform

Fdetimes; Redwood City (CA); On-site; USD 150,000 - 198,000; Full time

Job summary

C3 AI, a leading enterprise AI software company, seeks a seasoned software engineer with a focus on Generative AI to join our Generative AI team. You will contribute to building infrastructure and tools to advance state-of-the-art and deploy enterprise AI capabilities.

You will collaborate with product managers, data scientists and engineers to drive end-to-end ML pipelines and enable large-scale models in production across heterogeneous hardware, including GPUs and TPUs.

Qualifications

• Bachelor's degree in CS/CE or related fields; MS preferred.
• Excellent Python; Java and JavaScript experience preferred.
• Strong knowledge of data structures, algorithms, and OO/FP.
• ML expertise including deep learning; production ML experience.
• End-to-end project ownership.
• Strong listening and communication skills.
• Interest in Generative AI (LangChain, Semantic Kernel, Plugins).
• Minimum 3 years in a fast-paced software company.

Responsibilities

• Build systems and tools to enable Generative AI in applications using the C3 AI Platform.
• Enable scalable end-to-end ML pipelines in distributed hardware (GPUs, TPUs, etc.).
• Collaborate with data scientists to research and implement latest approaches to train/fine-tune Generative Models.
• Work with product owners to define and lead the long-term development the C3 Generative AI Suite.
• Mentor junior members of the team.

Skills

Python

Java

JavaScript

ML production

End-to-end ownership

Education

Bachelor's in CS/CE

MS preferred

Tools

LangChain

Semantic Kernel

ChatGPT Plugins

Job description

C3 AI, a leading enterprise AI software company, seeks a seasoned software engineer with a focus on Generative AI to join our Generative AI team. You will contribute to building infrastructure and tools to advance state-of-the-art and deploy enterprise AI capabilities.

You will collaborate with product managers, data scientists and engineers to drive end-to-end ML pipelines and enable large-scale models in production across heterogeneous hardware, including GPUs and TPUs.