Note: This post is for our recruiting events at selected universities only (Stanford, UT Austin). For general openings, please visit our Careers page.
About the CompanyBorn 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 RoleAs a Research / ML Engineer, you will play a crucial role in conducting and enabling cutting-edge research and translating it into our core product pipeline. You will work closely with other members of the technical staff to develop and improve state-of-the-art judges for safety, reliability, and data curation. Your technical skills will accelerate our research and ensure that our product remains at the forefront of innovation.
About YouThere are a few specific things we’ll be looking for that will help you succeed in this role:
Bachelor’s degree or equivalent practical experience
Experience in an industry research lab or equivalent academic experience
Strong background in machine learning systems, such as distributed training of large models and/or ML performance optimization
Knowledge of ML/AI applications and models, especially foundation models, how they are constructed, and how they are used
Experience contributing to research communities, including open-source research projects or publishing at conferences (e.g., CVPR, NeurIPS, ICCV/ECCV, BMVC)
Strong foundations in software engineering and empirical research
Ability to work separately and as part of a team. Excellent communication and presentation skills
We are working 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 degree or equivalent practical experience
- Experience in an industry research lab or equivalent academic experience
- Strong background in machine learning systems, distributed training, and ML optimization
- Knowledge of ML/AI applications, especially foundation models
- Experience contributing to research communities and open-source projects
- Strong foundations in software engineering and empirical research
- Excellent communication and presentation skills
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.
