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We build infrastructure that delivers massive amounts of web data to the companies training the world’s most powerful AI models.
We're the team that helps to power and support Grass, a bandwidth-sharing network that lets us operate a massive distributed crawler, giving us unique access to high-quality public web data at global scale. On top of that, we’ve built pipelines for ingesting, segmenting, and annotating billions of videos, transcripts, and audio files, powering dataset creation for frontier labs.
We’re lean, technical, and move fast. No red tape, no slow decision-making; just a team of builders pushing to expand what’s possible for open web data and AI.
Who You Are:
- Acts with integrity and seeks out responsibility
- Demonstrates resilience, resourcefulness, and motivation for getting things done
- Organized and process-driven
- Approaches challenges as opportunities
- Curious and challenges personal assumptions regularly
- Welcomes feedback and open dialogue
- Values team success over personal recognition
What You'll Be Doing:
- Build and improve backend code primarily in TypeScript.
- Set up and maintain metrics dashboards for production systems.
- Update existing code to support new metrics and improve system observability.
- Set up alerts and work closely with DevOps to optimize production systems.
- Automate deployments and operational reporting to Slack.
- Test systems in production, identify and troubleshoot issues, and fix bugs.
- Help clean up and improve the existing codebase.
- Write and maintain automated tests.
- Improve and optimize deployment processes.
- Implement code enhancements as new requirements emerge.
Skills, Requirements and Qualifications:
- Bachelor’s degree or equivalent work experience.
- 2+ years of experience in a backend software engineering role.
- Solid TypeScript development skills and strong backend software engineering fundamentals.
- Good understanding of metrics, monitoring, and alerting, with the ability to debug and troubleshoot production systems.
- Ability to write clean, maintainable, well-tested code and make reliable improvements to existing systems.
Nice to have:
- Experience with Go.
- Experience with Datadog, OpenObserve, and/or building Slack bots or integrations.
- Familiarity with web scraping and browser automation, including Playwright.
Why Work With Us:
- Opportunity. We are at the forefront of developing a web-scale crawler and knowledge graph that improves access to public web data and extends the value of AI to the people.
- Culture. We're a lean team with a high bar. We come to work not to be comfortable, but to find out what we're capable of and to do work that matters. We're not calling for people who keep things moving. We're calling for people who make everyone around them better.
We prioritize low ego and high output. This is a fully remote team. - Compensation. You’ll receive a competitive salary, benefits and equity package.
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Wynd Labs
View Company ProfileWynd Labs is a premier, enterprise-grade data infrastructure platform engineered to orchestrate massive-scale public web data ecosystems and intelligent artificial intelligence training workflows. Operating as a highly integrated decentralized data hub, the company eliminates the operational friction of traditional localized web scraping by seamlessly deploying advanced distributed crawling telemetry, rigorous multimodal data pipelines, and cohesive residential proxy architectures. Moving beyond rigid legacy dataset providers, Wynd Labs empowers frontier AI labs, elite research teams, and data-driven enterprises to dynamically synchronize their machine learning models with instantaneous, internet-scale data ingestion. Under the hood, their sophisticated backend infrastructure natively handles complex high-throughput routing, scalable real-time search extraction, and seamless petabyte-scale multimedia annotation, ensuring frictionless data accessibility and uncompromising model training readiness. What sets Wynd Labs apart is its uncompromising dedication to frictionless data orchestration; by bridging the gap between decentralized bandwidth sharing and rigorous artificial intelligence development, the platform empowers organizations to radically accelerate their algorithmic velocity, optimize data acquisition, and build an unassailable foundation for continuous AI dominance in the modern computational landscape.
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