Applied ML Scientist

Responsibilities

Within one month, you will…

• Start building a trusting relationship with your peers, and learning the company structure.
• Be set up to do local development, and be actively prototyping.
• Dive deep into how AI and ML is already used at Sourcegraph and identify ways to improve moving forward.
• Ship a substantial new feature to end users.

Within three months, you will…

• Be seen as a subject matter expert in all things AI at Sourcegraph.
• Be contributing actively to the world’s best coding assistant.
• Be following all the relevant research, and conducting research of your own.

Within six months, you will…

• Be fully ramped up and owning key pieces of the assistant.
• Be ramped up on other relevant parts of the Sourcegraph product.
• Be helping design and build what might become the biggest dev accelerator in 20 years.

About you 

You are a polyglot hacker in the AI/ML space who wants to be part of a world-class team to push the boundaries of AI, with a particular focus on leveraging Sourcegraph’s code intelligence to leapfrog competitors.

First, you have a deep understanding of programming languages, and tools that manipulate code. This could have taken any number of forms; e.g.:

• You’ve worked with grammars and parser generators, or Treesitter
• You’ve worked with compilers and semantic analysis, e.g. type systems
• You’ve written an interpreter, or worked on a virtual machine
• You’ve done static analysis involving scanning source code for semantic information

It doesn’t really matter how you know it, but it’s important that you’re familiar with the basic concepts of semantic representations of source code, and how they’re produced and consumed by tooling.

Second, your AI background could look like a few different things:

• You’ve worked on AI systems and have built ML at large tech companies.
• You have a deep ML background and have demonstrated an ability to be customer and company focused. You are hands-on and can build machine learning
• You are a Prompt Engineer and can take models and figure out how to speak to it in a way that yields different results
• You are an entrepreneurial engineer who can hack together prototypes quickly, get things out the door, and iterate
• You are an LLM hacker or a thought leader in the LLM space and can craft a roadmap that takes advantage of the space, especially with code intelligence
• You’ve worked in NLP or language models at a top-tier research lab