Open roles in Engineering teams, from every company on the board.
17 jobs found · Engineering
Bangalore, IndiaIndia & South Asia
As an Threat Research Engineer at GitLab, you'll research emerging security threats and turn your findings into protection for GitLab customers.
We're looking for a Machine Learning Engineer to join our Radius squad.
Bangalore, IndiaIndia & South Asia
As a Staff Backend Engineer, you will provide technical leadership across your team and adjacent teams, solving the highest-scope and most complex problems in your area.
San Francisco Bay AreaNorth America
This role works at the intersection of applied research, quality, and product engineering to make those systems better. It also means bringing emerging research into the…
This is an applied AI engineering role, not a traditional support role. When a customer needs direct engineering, you will debug and ship.
San Francisco Bay AreaNorth America
Our team owns data and evaluation science for Glean's AI products. Starting from real production usage, you'll turn what we learn into evals that guide improvements…
Bangalore, IndiaIndia & South Asia
Glean is looking for a Supply Chain Security Engineer with a primary focus on ensuring that our entire technology stack is free of software vulnerabilities (CVEs).
Mountain View, CANorth America
Glean’s Enterprise Brain team builds applied ML systems that help Glean understand a user’s work and anticipate useful next steps, including task prediction and…
Bangalore, IndiaIndia & South Asia
Glean is looking for engineers to help build the world’s best search and assistant product for work.
Remote · New York, NYNorth America
We're looking for a Senior Machine Learning Engineer to help shape the next generation of Search at Spotify.
Mountain View, CA; San Francisco, CANorth America
As the Tech Lead Manager of AI Evaluations, you will lead a team of applied AI scientists and engineers and build the evaluation strategy and platform that helps Glean…
This is a backend role focused on data management, working on the problems at the core of any large data platform: running a data catalog that stays accurate at scale…