Discovery Engineering at Outside turns Impact from our award winning content and passionate community into Active Moments. From planning a hike, learning a new yoga pose or registering for their first marathon - we are simplifying personalized Discovery for users. We guide Discovery every day by understanding the world of active choices better than anyone else.
We are looking for an Experienced Python Engineer to grow our team of active lifestyle participants who share a common interest in federated backend systems, their scalability and continued development. You will build the backend systems that power our recommendation system (recsys) and syndication platform, create collaborative solutions, and continuously improve our engineering practices. Above all, your work will personalize how the world Discovers their next Active Moment.
This job can be 100% remote
You are Energized by:
- Creating novel solutions, without reinventing the wheel
- Sharing how you’ve learned from what didn’t work
- Embracing standards that align teams
- Taking on new responsibilities for what you build
- Participating in code reviews, pairing and hackdays
- Organizing around work, not people (spending less time in meetings)
- Joining a rapidly scaling project
We are Excited to build together because You:
- Have demonstrated creativity in creating scalable API’s using Python and GraphQL
- Contributed to a new or an existing codebase, ideally in productionInvest time to increase your knowledge, in both foundations and abstractions of technology
- Care about user outcomesValue team success over personal success
- Embrace uncertainty and use it as an opportunity to learn
Entirely remote jobs that could be performed in Colorado: Employees can expect to be paid a salary of between $130,000 to $145,000. Additional compensation may include a bonus or commission . Additional benefits include health care, vision, dental, retirement, Flexible Time Away, sick leave, and more. This salary range is merely an estimate and may vary based on an applicant’s location, market data/ranges, an applicant’s skills and prior relevant experience, certain degrees and certifications, and other relevant factors
Data source
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