Degree in Computer Engineering
Large Language Models - LLMs, Machine learning techniques, Natural Language Processing (NLP), Statistics
Why this job is exciting
We are creating a machine learning team at Sourcegraph, aimed at creating the most powerful coding assistant in the world. Many companies are trying, but Sourcegraph is uniquely differentiated by our rich code intelligence data and powerful code search platform. In the world of prompting LLMs, context is everything, and Sourcegraph’s context is simply the best you can get: IDE-quality, global-scale, and served lightning fast. Our code intelligence, married with modern AI, is already providing a remarkable alpha experience, and you can help us unlock its full potential.
We are looking for a polyglot AI/ML hacker, versed in programming language semantics, with a strong AI/ML background, who can help us deliver the world’s best coding assistant, built on our mature, robust, and open code intelligence platform. And if you happen to have an entrepreneurial streak, you’re in luck: We have an enterprise distribution pipeline, so whatever you build can be deployed straight to enterprise customers with some of the largest code bases in the world, without all the go-to-market hassle you’d encounter in a startup.
You will be a scientist at Sourcegraph Labs doing R&D, and pushing the boundaries of what AI can do, as an IC on our new ML team. You will have the full power of Sourcegraph’s Code Intelligence Platform at your disposal, and you’ll be working on a coding assistant that is already awesome even after just a few weeks of work, so this is a greenfield opportunity to multiply dev productivity to unprecedented levels.
Within one month, you will…
Within three months, you will…
Within six months, you will…
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.:
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:
If you’ve been anywhere near the field lately, you can probably pick up enough about LLM capabilities to be able to drive this space, as it’s all greenfield.
Finally, you shouldn’t be a purist about languages. We may need to integrate the coding assistant into a wide variety of tooling contexts, each with its own programming language. You may find yourself writing in several programming languages along the journey, and hopefully you already know most of them a little anyway.
This job is an IC4. You can read more about our job leveling philosophy in our Handbook.
We pay you an above-average salary because we want to hire the best people who are fully focused on helping Sourcegraph succeed, not worried about paying bills. You will have the flexibility to work and live anywhere in the world (unless specified otherwise in the job description), and we’ll never take your location or current/past salary information into account when determining your compensation. As an open and transparent company that values equitable and competitive compensation for everyone, our compensation ranges are visible to every single Sourcegraph Teammate. To determine your salary, we use a number of market and data-driven salary sources and target the high-end of the range, ensuring that we’re always paying above market regardless of where you live in the world.
The target compensation for this role is $190,000 USD base.
In addition to our cash compensation, we offer equity (because when we succeed as a company, we want you to succeed, too) and generous perks & benefits.
Sourcegraph is a code intelligence platform that unlocks developer efficiency, helping engineers and engineering leaders understand, fix, and automate across their entire codebase. Over one million engineers use Sourcegraph to improve code security, efficiently onboard developers, promote code reuse, resolve incidents, and boost code health.