We are building a modern, human-centric infrastructure stack for machine learning.
Our roots are at Netflix, where we started Metaflow – an open-source framework that helps data scientists and ML engineers develop and deliver real-life ML projects. At Netflix, we saw that successful data science projects were delivered by data scientists and ML engineers who can work on end-to-end workflows independently, focusing more on data science, less on engineering.
Outerbounds provides a full stack for machine learning and data science based on Metaflow, which allows companies to experiment with new ideas rapidly and deploy to production frictionlessly. The stack empowers the data scientist to use their smarts and human creativity to the fullest: It allows them to execute compute-intensive jobs in the cloud, handle large amounts of data, and operate complex applications, iterating on projects quickly and confidently.
Over the past years, we have worked with hundreds of companies and over a thousand data scientists and engineers to make this a reality in their environments. We have heard and answered a myriad of questions which we have now started collecting on this site. Take a look and let us know if you notice an important topic or question missing.
We welcome you to join our Slack for support, feedback, and chat with likeminded data scientists and engineers. Also, if this vision resonates with you, we are hiring!
Work with us!
We believe that you will be happy and successful at Outerbounds if the following pre-requisites are met:
Do you have the right skill set and mindset, personal interest, and motivation to grow in a particular role?
Our overarching goal is to provide delightful and polished user experiences for our customers, including non-technical concerns like documentation and user support. Are you excited and energized by this overall vision and approach?
Not a jerk
We value humility, friendliness, thoughtfulness, and empathy highly. Will you thrive amongst colleagues like this?
Crucially, we are not evaluating you as a person. Even jerkiness can be a function of the environment and people around you, so we just need to evaluate the mutual match. Also, you can be an amazing individual with unique talents but we just don’t have a role for you today. For instance, as much as we might want to work with Barack Obama or Billie Eilish, we must honestly admit that we don’t have open roles that would make them or us happy currently. Maybe later!
As an early-stage startup, we don’t have clearly defined roles yet. At this point, everyone is expected to be involved in multiple efforts across the company. However, we know that there are dimensions of expertise that would complement our existing team and address our current business needs. Every individual has skills in each of these dimensions but we’d hope to hire people who clearly excel in at least one of the dimensions we are hiring for today.
Many companies call this hiring approach T-shaped. In the absence of clearly defined roles, we can loosely think that the leg of the T is the primary “role” that we are hiring you for. However, we don’t pigeonhole anyone based on a single strength: We love to support you in deepening other areas of your expertise and growing more legs for your T. A great thing about startups is that there will be many opportunities to learn and push the outer bounds of your expertise.
Below is a list of dimensions that we are looking for at the moment and the characteristics that define them. Note that the bullet points are not a list of requirements for every individual but rather a set of prototypical data points that help to identify the dimension.
- Years of experience in contributing to non-trivial Python projects.
- Good sense of aesthetics: What makes a project Pythonic.
- Understand how Python / Unix-like operating systems work internally.
- Experience with different types of Python projects: notebooks, web servers, CLI apps, scripts, etc.
- Understand the performance characteristics of Python / computers in general: How to make things slow vs. fast.
- Years of experience in building modern DevOps tools & best practices: CI/CD systems, deployment tools (CloudFormation, Terraform, Pulumi, etc)
- Deep expertise with the cloud, AWS in particular.
- Experience with K8S.
- Understanding of security/auth constructs and requirements.
- Understanding of networking constructs and requirements.
If this sounds interesting, we would love to hear from you – firstname.lastname@example.org.