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Engineering Lead/Manager - Ought - San Francisco or Fully Remote







3 months

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Engineering Lead/Manager - Ought - San Francisco or Fully Remote

Location: Type: Full-time

Position: Engineering Lead/Manager

Salary: $150K-$200K (dependent on work location & level of experience)

Location: San Francisco, CA or Fully Remote anywhere in the US

Ought is an applied research lab building Elicit, a GPT-3-based research assistant for questions about the future.

Today, researchers and policy analysts use Elicit to find relevant publications for a literature review, find datasets, or brainstorm research questions that are interesting to their audience. Researchers can define new tasks by showing Elicit just a few examples of the task being done. Elicit then scales those tasks to thousands of publications and datasets.

The Role and Your Impact:

  • Manage the work of at least 2-3 other engineers

  • Contribute directly to the Elicit codebase

  • Help design the technical product and roadmap

  • Make key architectural decisions, such as how to

    • Compose together multiple calls to language models to accomplish tasks that we can't accomplish with a single call, as in this paper

    • Connect Elicit with external data sources such as spreadsheets and site searches

    • Let users quickly provide feedback to the tool to create an interactive training loop

  • Help build out the engineering team

What You May Bring:

  • A strong software engineering background. We want to apply your experience building systems, designing architecture, and thinking about good abstractions. Most people who are a good fit for this role will have 4+ years of experience in software engineering roles.

  • 2+ years of experience managing a small team, squad, or project with at least 3-5 other engineers in various roles.

  • Ability to reason about and choose among different frameworks, cloud services, and libraries.

  • Clear communication about engineering topics to diverse audiences.

Bonus If You Have:

  • Familiarity with language models (training, fine tuning, evaluation) or natural language processing more generally

  • A startup mindset. We expect to measure our impact in part by the people whose lives we improve through reasoning and models of the future.

  • Experience with functional programming (e.g. SICP), programmable software (e.g., Emacs, Vim), or symbolic AI (e.g. PAIP).

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