At Generally Intelligent, we take recruiting seriously and take great measures to optimize our process for the benefit of both our team and the candidate. To this end, we are seeking a personable and proficient coder to conduct first-round coding interviews on behalf of our team. You would be responsible for Step 2 in the interview process outlined here. This can be either a full-time or a contract-based, hourly position and is ideal for junior engineers looking to improve their skills.

• You are strong in the fundamentals of computer science including algorithms and data structures

• You are proficient in Python and ideally comfortable with 2–3 other languages

• You have an eye for clean, debuggable code and good coding practices

• You are comfortable on video calls (strong wifi and professional interview setting are a must)

• You are able to appropriately guide candidates when they get stuck

• You can commit to a minimum of 20 hours a week

• We will train you on 3 coding problems that you will present to candidates

• You will observe candidates coding in their own environment using whatever resources, libraries, or frameworks they’d like

• You will then submit feedback on the candidate’s performance and a recording of the interview through our ATS (Applicant Tracking System)

All submissions are reviewed by a person, so we encourage you to include notes on why you’re interested in working with us. If you have any other work that you can showcase (open source code, side projects, etc.), certainly include it! We know that talent comes from many backgrounds, and we aim to build a team with diverse skillsets that spike strongly in different areas.

We try to reply either way within a week or two at most (usually much sooner).

We started Generally Intelligent because we believe that software with human-level intelligence will have a transformative impact on the world. We’re dedicated to ensuring that that impact is a positive one.

We have enough funding to freely pursue our research goals over the next decade, and our backers include Y Combinator, researchers from OpenAI, Astera Institute, and a number of private individuals who care about effective altruism and scientific research.

Our research is focused on agents for digital environments (ex: browser, desktop, documents), using RL, large language models, and self supervised learning. We’re excited about opportunities to use simulated data, network architecture search, and good theoretical understanding of deep learning to make progress on these problems. We take a focused, engineering-driven approach to research.