Born from the understanding that AI deployment shouldn't require months of preparation or compromise on quality, we've built a comprehensive platform that turns your brand values into production-ready AI applications in days, not months.
Our product is AI Judges that are trained with proprietary auto-align technology and powered by state-of-the-art research on Alignment and RL. We help companies build AI systems that aren't just safe and reliable, but truly aligned with their brand values and business objectives.
Backed by top-tier Silicon Valley venture capital firms, we're on a mission to make safe, reliable, and highly-performant frontier AI for enterprise use-cases a reality.
Join us in pushing the boundaries of what's possible in AI! Learn more about the company here.
About the RoleWe are looking for a talented Software Engineer (Machine Learning) with expertise in React and NextJs (JavaScript frameworks) for frontend development and backend development in Python and Fast API. The ideal candidate will have hands-on experience in DevOps technologies, testing frameworks, database management, and exposure to AI/ML or NLP/LLM projects.
Key responsibilities include:
Develop scalable, responsive web applications using modern frontend frameworks (React/Next.js)
Design and implement high-performance backend solutions using Python and FastAPI, ensuring reliability and scalability
Collaborate with cross-functional teams to define features, enhancements, and deliver product updates
Implement and maintain DevOps best practices for continuous integration and deployment using tools like Jenkins, AWS, Docker, and Kubernetes
Write and maintain comprehensive unit, integration, and end-to-end tests using testing frameworks
Troubleshoot and debug frontend and backend issues, ensuring timely resolution and system optimization.
Work with both SQL and NoSQL databases, optimizing queries for efficient data management
Collaborate with AI/ML teams to build and deploy applications leveraging NLP and LLM technologies
There are a few specific things we’ll be looking for that will help you succeed in this role:
Bachelor’s or Master’s degree in Computer Science/Engineering, or a related field
Experience in full stack development with a focus on both frontend and backend technologies
Proficiency in JavaScript frameworks (React/Next.js) for frontend development
Strong backend development skills in Python (FastAPI) or similar languages
Experience with DevOps tools such as Jenkins, AWS, Docker, and Kubernetes for CI/CD pipelines
Hands-on experience with testing frameworks and a Test-Driven Development (TDD) approach
Expertise in SQL and NoSQL databases, with a solid understanding of database design and optimization
Experience in AI/ML or NLP/LLM projects is highly desirable
Contributions to open-source projects, with an active GitHub portfolio showcasing innovation and expertise, are preferred
Strong problem-solving skills and the ability to work in a fast-paced, collaborative environment
Prior experience in top-tier technology companies or startups is a plus
We are working with leading global enterprises to deliver cutting-edge AI safety and reliability tools. And we are looking for brilliant, high-agency, low-ego rockstars to join us on this crusade. We want the best of the best and firmly believe greatness begets greatness.
Come here to push yourself hard, learn things fast, experience unmatched excellence, and do your life's work.
Skills Required
- Bachelor's or Master's degree in Computer Science/Engineering or related field
- Experience in full stack development
- Proficiency in JavaScript frameworks (React/Next.js)
- Strong backend development skills in Python (FastAPI)
- Experience with DevOps tools such as Jenkins, AWS, Docker, and Kubernetes
- Hands-on experience with testing frameworks and TDD approach
- Expertise in SQL and NoSQL databases
- Experience in AI/ML or NLP/LLM projects
- Contributions to open-source projects
- Prior experience in top-tier technology companies or startups
What We Do
Collinear AI builds simulation labs where AI agents learn to work in the real world by simulating users, tools, and workflows to improve AI models before deployment, focusing on AI safety, reliability, and customization for enterprise GenAI.









