Software Engineering Intern
Tractian
Atlanta, GAFresher1h agovia LinkedIn
About the Role
Tractian combines hardware, software, and AI to help industrial teams detect equipment problems early and prevent costly downtime. Our technology supports over 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.
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, working through implementation, testing, and review to learn how product requirements become reliable software.
Key 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 & Tech Stack
- 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 an explainable project.
- Understanding of data structures, APIs, and databases, with experience using Git and testing your own code.
- Experience using AI coding tools (agent harnesses, skills, MCP integrations), including reviewing and testing their output.
- Ability to investigate unfamiliar problems, explain tradeoffs, and improve 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.
What You Will Gain
- Hands-on experience building AI and machine-learning applications for industrial intelligence.
- Mentorship from engineers and data scientists on 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.