<aside> ⬅️ Learn more about Dryft and our recent funding from General Catalyst, Neo and people like Jeff Wilke (former Amazon CEO) & Claire Hughes Johnson (former Stripe COO).

</aside>

This role is in person in San Francisco with the option to work temporarily remote.

About you

As our backend founding engineer, you’ll be the brain behind Dryft’s decision intelligence. Think of yourself as the mastermind in a high performance sports team.

Your highest priority is to develop and maintain robust, scalable Python-based backend services that are core to our decision intelligence. This includes developing pieces of the core logic for our decision model and the required data pipelines to enable intelligent decision making. You collaborate closely with our CTO to deliver high-quality, efficient code.

You are right for this role if you consider yourself a world-class:

Builder: You ship code, fast. This also shows in your experience.
Problem-solver: You are persistent and find new ways to tackle challenges at the frontier of technology also if this means finding the hack that gets you to the goal.
System-thinker: You know your frameworks & best practices to build a robust, scalable application.

Responsibilities

🎨 Build: Design, develop, and deploy robust Python-based backend services using Django. Craft crucial components that power our decision intelligence model, shaping the core of our product's decision-making capabilities.
🛣️ Data Processing: Implement robust data processing and storage solutions crucial to out core logic (we are moving a lot of data!)
🛠 Performance: Ensure high uptime, seamless service integration, and monitor system health. Optimize frontend-backend synergy.

Qualifications

Backend Excellence: 4+ years in Python-focused backend development. Expertise in Python web frameworks (Django, Flask, or FastAPI). Proficient in microservices and software design principles. Deep knowledge of SQL, NoSQL databases as well as experience building data pipelines.
Strong ML Expertise: Solid understanding of both deterministic and machine learning algorithms with experience in writing, debugging, and optimizing model prototypes for both deterministic and stochastic approaches; proficiency in Pytorch.
DevOps Expertise: Expertise in CI/CD, cloud platforms (preferably Azure), and modern DevOps practices.
Full Stack Experience: Ability to develop end-to-end prototypes by yourself. Ability to collaborate closely with Front-end engineers for larger applications