About the Position

As a Reasoning engineer, you will build frameworks to improve the reasoning capability, build distributed reinforcement learning systems, techniques for inference time compute (e.g. tree search and planning), and develop environments for agents.

You will get exposure and will be expected to solve and take ownership of components across the entire stack.

Tech Stack

• Python
• JAX
• Rust

Location

The role is based in the Bay Area [San Francisco and Palo Alto]. Candidates are expected to be located in the Bay Area or open to relocation.

Focus

• Build robust and scalable distributed RL systems.
• Optimize frameworks to enable complex inference-time reasoning.
• Develop environments and harnesses for agents.

Ideal Experiences

• Experienced with large-scale reinforcement learning systems.
• Designing and implementing distributed systems.
• Keeping up with state-of-the-art RL and inference time compute algorithms.

Interview Process

After submitting your application, the team reviews your CV and statement of exceptional work. If your application passes this stage, you will be invited to a 15 minute interview (“phone interview”) during which a member of our team will ask some basic questions. If you clear the initial phone interview, you will enter the main process, which consists of four technical interviews:

1. Coding assessment in a language of your choice.
2. Systems hands-on: Demonstrate practical skills in a live problem-solving session.
3. Project deep-dive: Present your past exceptional work to a small audience.
4. Meet and greet with the wider team.

Our goal is to finish the main process within one week. We don’t rely on recruiters for assessments. Every application is reviewed by a member of our technical team. All interviews will be conducted via Google Meet.

Annual Salary Range

$180,000 – $440,000 USD