- 100% remote
- You decide your working hours
- Complete ownership of projects
- No micromanaging whatsoever
- Exciting unsolved engineering problems
- You will build with the CTO daily and directly report to our CEO
- Huge growth and leadership potential. As engineer #1 of the company, we want you to soon manage a team of engineers and eventually replace our CTO
- Top 1% problem solving
- Top 1% in learning speed, our CTO will train you directly
- Desire to lead a team of engineers in the future
- We are an international team, international applicants are OK
- Python
- Typescript
- Chrome extensions
- NLP
- React
- Django
- PostgreSQL
- GCP
- LLMs
- General AI understanding
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Full-Stack Engineer - Garden City, United States - Patterned Learning AI
Description
Job DescriptionFull-Stack Engineer- Remote Job, 1+ Year Experience
Annual Income: $60K - $65K
A valid work permit is necessary in the US/Canada
About us: Patterned Learning is a platform that aims to help developers code faster and more efficiently. It offers features such as collaborative coding, real-time multiplayer editing, and the ability to build, test, and deploy directly from the browser. The platform also provides tightly integrated code generation, editing, and output capabilities.
About the job
Our AI startup has been featured on VICE, New York Times, Futurism, Fox News, and more for disrupting our industry. We are hiring our first engineer
We still operate in stealth so we aren't able to discuss exactly what we do until you are selected for an interview directly with our CTO, but here is what we can share:
Why you should join us
Useful technical skills (not required)
Why Patterned Learning LLC?
Patterned Learning can provide intelligent suggestions, automate repetitive tasks, and assist developers in writing code more effectively. This can help reduce coding errors, improve productivity, and accelerate the development process.
The pattern recognition is particularly relevant in the context of coding. Neural networks, especially deep learning models, are commonly employed for pattern detection and classification tasks. These models simulate human decision-making and can identify patterns in data, making them well-suited for tasks like code analysis and generation.