AI Infra Engineer - Serverless LLM

Job Summary

We are seeking AI Infra Engineer to design, develop, and optimize distributed AI systems for serverless AI platforms. The successful candidate will leverage expertise in large language models (LLMs), and system design to build robust, scalable solutions. This role offers a unique opportunity to contribute to innovative AI-driven systems, collaborating with cross-functional teams to deliver high-impact solutions in a fast-paced, research-driven environment.

Key Responsibilities

• Design and implement scalable, distributed systems to support AI-driven workloads, ensuring high performance and reliability.
• Develop robust software solutions using Python (and potentially C++) to address complex technical challenges in AI and distributed computing.
• Work within a larger team to rapidly develop proof-of-concept prototypes to validate research ideas and integrate them into production systems and serverless infrastructure.
• Work closely with cross-functional teams to participate in developing innovative AI infrastructure, data systems, and cloud computing technologies.
• Implement resource scheduling and orchestration mechanisms to ensure efficient execution of distributed tasks.

Required:

• Education: Bachelor's or Master's degree in Computer Science or a related technical field. (PhD preferred but not required).
• Have an in-depth understanding of distributed systems and/or cloud computing and/or ML systems and/or multi-agent systems.
• Have an in-depth understanding of serverless platforms and containerization (e.g., Docker, Kubernetes).
• Good programming skills, master of at least one language, such as Python, and/or C/C++.
• Good communication and teamwork skills.

Desired:

• PhD in computer science, distributed systems, machine learning, or a related field.
• Experience in the full lifecycle of developing, deploying, and maintaining large-scale cloud production systems, demonstrating expertise in scalability, reliability, and performance optimization