Degree in Computer Engineering
AI technology, 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 has a unique advantage: Our rich code intelligence data and powerful code search platform. In the world of prompting LLMs, context is key, 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 code-assistant experience. You can help us unlock its full potential, delivering a product that accelerates development in a way we only see every 10-15 years.
To head up this effort, we are looking for a seasoned and deeply technical engineering leader, versed in programming language semantics, with a strong AI/ML background and familiarity with recent techniques, who can help us deliver the world’s best coding assistant and ML-powered developer tooling, built on Sourcegraph’s 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 codebases in the world, without all the go-to-market hassle you’d encounter in a startup.
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 build and lead 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 in 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 M4. 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 $243,000 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.