Why Join Us
Tractian combines hardware, software and AI to help industrial teams detect equipment problems early and prevent costly downtime. Our technology supports more than 3,761 plants and monitors over 370,000 industrial assets. As a Y Combinator company, we’ve been recognized on the Forbes AI 50, named a G2 Leader and ranked No. 24 on Deloitte’s Technology Fast 500 in North America. Join us to help build technology that keeps industry running.
Software at Tractian
Our software connects machine data with the decisions maintenance teams make every day. Engineers build the applications, services and integrations behind equipment monitoring and maintenance management.
What You Will Do
Build a defined feature or service with our engineering team. You will work through implementation, testing and review, learning how product requirements become software that people can rely on.
Responsibilities
- Develop frontend components or backend services for an application, internal tool or product demonstration.
- Build APIs and connect databases or data workflows, with attention to validation and error handling.
- Write automated tests, debug failures and improve performance using logs and reproducible examples.
- Participate in code reviews, document technical decisions and collaborate with product and engineering partners.
Requirements
- Pursuing or recently completed a bachelor's or master's degree in Computer Science, Software Engineering, Computer Engineering or a related field.
- Strong programming ability in Python, TypeScript, JavaScript, Go or C++, demonstrated through a project you can explain in depth.
- Understanding of data structures, APIs and databases, with experience using Git and testing your own code.
- Experience using AI coding tools, including agent harnesses, skills and MCP integrations, while reviewing and testing the code they produce.
- Ability to investigate unfamiliar problems, explain tradeoffs and improve your work through feedback.
Helpful Experience
Experience with React, Node.js, FastAPI, SQL, Docker or cloud deployment. Exposure to ML integration or IoT data is useful; depth in one working project matters more than a long tool list.
What You Will Gain
- Hands-on experience building AI and machine-learning applications that power industrial intelligence.
- Mentorship from engineers and data scientists solving production-level challenges.
- Exposure to predictive-maintenance analytics and industrial machine learning.
- A chance to help shape the future of smart maintenance and industrial AI.