Infrastructure Engineer - Scalable ML Systems

Bison; San Francisco (CA); Presencial; USD 300.000 - 400.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health, dental, and vision benefits

Unlimited PTO

Paid parental leave

Relocation support

Descripción de la vacante

Thinking Machines is hiring a Software Engineer, Infrastructure to design and build the distributed systems powering our model training and serving platforms. You will own systems that run at large scale and help research and product teams iterate quickly.

Responsibilities span orchestration, scheduling, storage, and resource management, with emphasis on reliability and observability. Proficiency in Python and Go will be essential in building internal libraries and APIs.

Formación

• Demonstrated expertise designing and developing large-scale distributed systems.
• Strong proficiency in Python and Go.
• Experience building, deploying, and operating production infrastructure at scale.
• Solid grounding in distributed systems fundamentals, such as consensus, consistency, fault tolerance, and networking.

Responsabilidades

• Design, build, and operate distributed systems that support large-scale model training and inference across thousands of accelerators.
• Build and maintain core infrastructure, including orchestration, scheduling, storage, and resource management systems.
• Improve the reliability, performance, and observability of infrastructure used across research and product teams.
• Partner with researchers and platform engineers to understand infrastructure needs and turn them into robust, well-abstracted systems.
• Debug and resolve complex distributed failures across the stack, from networking and storage to compute and scheduling.
• Write and maintain internal libraries and APIs, primarily in Python and Go, that other engineers build on.

Conocimientos

Distributed Systems

Python

Go

APIs

Production Infrastructure

Herramientas

Kubernetes

Descripción del empleo

Thinking Machines is hiring a Software Engineer, Infrastructure to design and build the distributed systems powering our model training and serving platforms. You will own systems that run at large scale and help research and product teams iterate quickly.

Responsibilities span orchestration, scheduling, storage, and resource management, with emphasis on reliability and observability. Proficiency in Python and Go will be essential in building internal libraries and APIs.