Founding ML Infra Engineer — Production-Grade LLMs

Realmlabs; Sunnyvale (CA); Presencial; USD 210.000 - 350.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Market aligned compensation

Founding engineer equity

Medical, Dental, Vision, and Life insurance

401-K

In-office lunch

Descripción de la vacante

An innovative AI startup is seeking a Founding ML Infrastructure Engineer to take charge of deploying and optimizing production-grade LLM systems. In this core role, you will be responsible for building and managing a full ML serving stack, working closely with product teams to ensure system performance and reliability. The ideal candidate will have extensive experience in ML infrastructure, particularly with LLMs, and will be proficient in relevant technologies such as PyTorch, TensorFlow, and Kubernetes. This position offers a unique opportunity to shape the future of AI within the company.

Formación

• Extensive experience with GPU inference technologies.
• Proficient in building production-grade ML infrastructure.
• Keen awareness of latency and throughput optimization.

Responsabilidades

• Own the end-to-end LLM inference stack.
• Design high-performance LLM serving systems.
• Collaborate with product teams for deployment.

Conocimientos

Deep understanding of LLM internals

GPU inference optimization

Software engineering fundamentals

Collaboration with cross-functional teams

Educación

5+ years of professional experience in ML infrastructure

Herramientas

PyTorch

TensorFlow

TensorRT

Triton Inference Server

Kubernetes

Descripción del empleo

An innovative AI startup is seeking a Founding ML Infrastructure Engineer to take charge of deploying and optimizing production-grade LLM systems. In this core role, you will be responsible for building and managing a full ML serving stack, working closely with product teams to ensure system performance and reliability. The ideal candidate will have extensive experience in ML infrastructure, particularly with LLMs, and will be proficient in relevant technologies such as PyTorch, TensorFlow, and Kubernetes. This position offers a unique opportunity to shape the future of AI within the company.