Software Engineer, Full Stack
Rad AI- Full Time
- Junior (1 to 2 years)
Candidates should possess at least 4 years of professional experience as a generalist software engineer, with demonstrated experience building both frontend and backend components of software products or internal tools. They should have experience with React and its core principles, proficiency in TypeScript or JavaScript, familiarity with Python, Go, Java, or another backend technology, and a strong foundation in data structures and algorithms with a focus on performance optimization. Experience with AWS and NodeJS is required, and familiarity with other cloud platforms and frontend build tools such as Webpack or Vite is preferred. Knowledge of ML concepts and frameworks like TensorFlow, PyTorch, or Spark is highly desired.
The Full-Stack Software Engineer will leverage their experience to create high-quality, scalable, and maintainable code and APIs, contributing to architectural decisions and participating in code and design reviews. They will employ their understanding of developer tools to influence the development of user-centric features for data scientists and engineers, and demonstrate excellent communication skills while working as part of a team to solve large and ambiguous problems independently. They will occasionally travel to the U.S. for extended durations to support collaboration and innovation.
Managed platform for ML and data orchestration
Union.ai offers a managed platform for machine learning (ML) and data pipeline orchestration, with its main product, Flyte, designed to handle complex workflows using Python code. Union Cloud simplifies the deployment and management of Flyte, allowing ML engineers and data scientists to focus on their work without worrying about infrastructure. The company serves a range of clients, including large enterprises, and operates on a subscription-based model for its services. Union.ai's goal is to accelerate ML projects by automating processes involved in model development and deployment, resulting in faster time-to-market.