ML Inference Engineer – Terminal-Bench Task Designer (vLLM / SGLang / TensorRT-LLM)

Remote, Worldwide

Overview

We are building a benchmark that tests how well AI agents handle real expert work in a terminal. We are hiring ML inference and serving experts to turn real, paid tasks from their jobs into expert-level Terminal-Bench challenges. Each task includes the environment, a working solution, and an automated check that proves the result is correct.

***THIS IS A TASK BASED COMPENSATION MODEL. PLEASE CHECK THE APPLICATION QUESTIONS FOR MORE DETAILS.***

Responsibilities

• Design expert-level Terminal-Bench tasks that turn real, paid ML inference work from your own experience into challenges an AI agent must solve end to end.

• Define the files, systems and environments each task runs on, such as model serving with streaming, so the challenge is realistic, reproducible and command-line solvable.

• Write a working reference solution for every task and verify it runs end to end, sized for about 60 to 75 minutes of expert effort.

• Build automated checks that objectively prove a result is correct, including cases where ML outputs go wrong silently, such as numerical drift or metric bugs.

• Package tasks with Docker and Git so they are reproducible, and document the systems,...