ML Engineer [IC3]

Who we are

Our mission at Sourcegraph is to make it so that everyone can code, not just ~0.1% of the population.

Everything is changing in how software gets built, and Sourcegraph builds tools that make it easier at scale. Code Search helps devs explore and understand massive codebases. Amp, our agentic coding tool, dramatically accelerates the time it takes to write new code and tackle complex problems like migrating and transforming code.

We’re trusted by engineering teams at leading companies like Stripe, Uber, and Palo Alto Networks, and with $225M in funding from investors like a16z, Sequoia, and Redpoint, we are building the tools that will define the next era of enterprise software development. We’re a globally distributed team with a culture of high agency, direct communication, and deep love for developers.

If you want to work at the bleeding edge of software and do the most meaningful work of your career, join us.

Hours & location

🌎 While we hire almost anywhere in the world, we have office hubs in select locations and expect this person to reside in the San Francisco Bay Area to be able to work from our office for several days per week.

Required locations:

• San Francisco, CA

We do not subscribe to “I do my best work when I work 40 hours a week.”  People we hire at Sourcegraph believe that building outstanding things means working very hard — smarter and more hours than the competition.

Why this job is exciting

How humans build, create, and work together is changing. Everything is changing. And today’s frontier models are just the beginning.

Amp is one of the highest quality coding agents available. You will be designing for the people who choose Amp, meeting their high expectations in every interaction

📅 Within one month, you will…

• Familiarize yourself with all corners of Amp, absorbing the norms.
• Familiarize yourself with how we build Amp

📅 Within three months, you will…

• Building out feature computation, storage, monitoring, analysis and serving systems for features required across our LLM stack
• Be contributing actively to the world’s best coding agents.
• Developing distributed training & experiment infrastructure over Code AI datasets, and scaling distributed backend services to reliably support high-QPS low latency use cases.
• 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 agents.
• 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.
• Owning a number of ML systems, and building core data and model metadata systems powering the end-to-end ML lifecycle.
• Be developing a highly scalable, high-QPS inference service providing low latency performance using a mix of CPU and GPU hardware to most efficiently utilize resources.
• Be driving the technical vision and owning a couple of major ML components, including their modeling and ML infra roadmap.

About you 

You are an experienced full-stack ML engineer with demonstrated industry experience in formulating ML solutions, developing end-to-end data orchestration pipelines, deploying large-scale ML models, and experimenting offline and online to drive business impact for Sourcegraph users. You want 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.

• You have 5-8 years of industry experience
• You are a backend focused ML engineer who has worked on the entire ML lifecycle
• You have deployed ML models to production to users and have developed feature pipelines
• You understand the nuances of ML for users to move metrics forward

Level

📊 This job is an IC3.  You can read more about our job leveling philosophy in our Handbook.

Compensation