Senior Python Backend Engineer
Reef Technologies · Technology
seniorRemote
Salary Range (USD)
$45 - $70
Location
Location N/A
Visa Support
Not mentioned
Funding Stage
Unknown
Job Responsibilities
- • Develop and maintain a trustless supercluster of GPU-enabled sandboxed Docker container runners.
- • Work on decentralized algorithms for container orchestration.
- • Contribute remotely from any location within EMEA/APAC.
- • Commit at least 30 hours per week and manage own time schedule.
Required Skills
PythonBackend developmentDockerGPU computing5+ years programming experience1+ year Python experience
Engineering Culture & Tech Stack
PythonDockerGPU
remote-first
self‑managed time commitment
sociocracy 3.0 decision‑making
decentralized architecture
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Senior Python Backend Engineer | REMOTE (EMEA/APAC)
We're looking for Python backend engineers to work on a trustless supercluster of performance-proofed GPU-enabled sandboxed docker container runners controlled by truly decentralized algorithms (not just PAXOS or RAFT).
Wow, that was a mouthful...
If you found it interesting, join Reef Technologies and tackle complex technical challenges like this on your own terms:
- Contribute from wherever you like; we are fully remote
- Set your own time commitment, as long as it's at least 30h per week
- See how we work in our handbook: github.com/reef-technologies/handbook
- Influence the way we operate through our Sociocracy 3.0 decision-making process
Salary on a B2B contract:
- 45-70 USD or 180-280 PLN per hour
- Flexible work schedule (as measured with a time tracker)
- We automatically adjust rates based on inflation twice a year
We're looking for someone with 5+ years of programming experience, including at least a year with Python (including open-source and significant personal projects).
So, what do you think? You don't even need a CV; just go to https://careers.reef.pl/?utm_source=hackernews and shoot a few quick commands to apply.
Edit: If you applied and haven't heard back, please check the spam folder of the email associated with the GitHub account you used to apply — our replies sometimes end up there.
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Content parsed by LLM from Hacker News raw data. Confidence:HIGH