Head of ML Infra, Sourcegraph
$243k
Universal code search for developers
Job no longer available
Universal code search for developers
101-200 employees
Job no longer available
$243k
101-200 employees
Company mission
To make it so everyone codes by building the tools that keep developers at the bleeding edge.
Role
Who you are
- You’re deeply familiar with at least one end-to-end system for ML pipelines at scale, and you are broadly familiar with the competition in the space and what options are available, and when
- In an ideal world, you are most deeply familiar with GCP’s machine learning stack, and you have a lot of practice operationalizing PyTorch experiments on that stack. It’s also great if you have Apache Spark in general
- You should be the kind of person who lives and breathes GPUs, and you should come armed with opinions about how best to deploy and cost-optimize Cody for our various customer classes, from large enterprises to casual hackers, particularly when it comes to the Cloud-side deployments
- In a perfect world, you would already be comfortable with options that enterprise customers might want for self-hosted ML infra, for running their own pipelines, e.g. other Cloud-hosted offerings, and/or OSS. Although we are pushing hard to have everything on GCP, the market is evolving rapidly and we could, for instance, come across customers who want to provide their own GPUs
- Any familiarity you have with deploying enterprise SaaS is a huge bonus because it is a part of the role. However, it’s something that you can pick up if you are already familiar with Cloud options
- Bonus if you have any background in graph theory or anything that would be relevant to our code graph, which plays a key role in the production of both training data and in acting as a source of truth for verifying model outputs
- We would love it if you are actively following developments in open-source models and training systems, and can come prepared with opinions about when and to what extent we should adopt them. Or more importantly, how we set up infrastructure that will tell us when they are ready, by evaluating their performance on Cody tasks
What the job involves
- Meet your team, which consists initially of 3 to 5 ML engineers (2 already on the team)
- Start building a trusting relationship with your direct reports and peers
- Come up to speed on the current state of machine learning in the Cody ecosystem
- Be set up for local development and familiar with Cody’s architecture
- Define our short-term roadmap for ML Infrastructure on GCP
- Ship a substantial feature, experiment, or evaluation
- Set up the at-scale infrastructure for running benchmarks that compare coding assistants
- Have defined a strategy for how we will address getting GPUs at scale for various personas
- Have defined a rough roadmap for how to cost-optimize our ML spend
- Have defined our on-prem/self-hosted roadmap and recommended configurations for ML infra
- Be up to speed and driving Sourcegraph’s ML Infra strategy
- Have hired a world-class team of ML engineers
- With the help of our research team, have delivered a ML-driven quality, benchmarking, and evaluation framework for coding assistants that runs at scale
- Have established a longer-term roadmap that keeps us aligned with expected advances in LLMs
- Be running dozens to hundreds of experiments with prompting, embedding, fine-tuning and other techniques
- 🌎 Given that we are an all-remote company and hire almost anywhere in the world, we don’t have a particular time-zone preference for this role. However, you may need to be available for non-recurring urgent meetings outside of working hours
Application process
- 👋 Introduction Stage - we have initial conversations to get to know you better…
- [30m] Recruiter Screen with Grace Bohl
- [45m] Technical Background with Beyang Liu
- [30m] Hiring Manager Screen with Steve Yegge
- 🧑💻 Team Interview Stage - we then delve into your experience in more depth and introduce you to members of the team…
- [60m] Resume Deep Dive with Grace Bohl
- [45m] Technical Deep Dive with Dominic Cooney and Julie Tibshirani
- [60m] Peer Interview with Erika Rice Scherpelz and Chris Pine
- [Async] Pairing Exercise with the team
- 🎉 Final Interview Stage - we move you to our final round, where you meet cross-functional partners and gain a better understanding of our business and values holistically…
- [30m] Values Interview
- [30m] Leadership Interview with Quinn Slack
- We check references and conduct your background check
- Please note - you are welcome to request additional conversations with anyone you would like to meet, but didn’t get to meet during the interview process
Our take
Inspired by code search engines like OpenGrok, Livegrep and Google Code Search, Sourcegraph has developed a robust tool that allows developers to swiftly search through code across an entire organization. While similar systems are used by large-scale organizations, Sourcegraph aims to make this powerful code search capability accessible to every developer.
Searching through extensive codebases, especially during debugging, can be time-consuming and tiresome. Sourcegraph streamlines this process, saving time and reducing stress for both individuals and businesses. The platform offers a free version for all developers, while revenue is generated through enterprise-specific features tailored for large corporations.
The launch of Cody, an open-source AI tool that enhances coding practices, saw the company expand into AI coding agents - although this part of its business is now splitting off into "Amp". This leaves the Sourcegraph team to focus on delivering and innovating its code search product, which is now a mission-critical piece of AI infrastructure software for many businesses.
Steph
Company Specialist at Welcome to the Jungle
Insights
-20% employee growth in 12 months
Company
Funding (last 2 of 5 rounds)
Jul 2021
$125m
SERIES D
Dec 2020
$50m
SERIES C
Total funding: $223m
Company benefits
- Medical, dental and vision (100% company-paid)
- Unlimited PTO with a 30 day minimum
- Wellness stipend
- Generous travel budgets
- Family planning benefits
- Equity
- Office budget
- Professional development
- Global, remote-friendly team with hubs in key cities
Company HQ
SoMa, San Francisco, CA
Leadership
Quinn Slack
(Board Member & Co-founder)CEO and Member of Technical Staff at Amp Code. Previously co-founded Blend Labs, and also worked at Palantir Technologies where they created a technology platform to help two of the top five U.S. banks recover from the housing crisis.
Beyang Liu
(CTO & Co-founder)Previously a Software Engineer at Palantir Technologies, where they developed new data analysis software on a small, customer-facing team working with Fortune 500 companies. Studied Computer Science at Stanford.
Dan Adler
(CEO)Joined the company in 2016 as Director of BizOps and Strategy. Became VP of Business in 2018, then CEO in 2025. Previously founded Cells Software, was an Investment Associate at Vector Capital, and Consultant at Bain & Company.
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