Member of Technical Staff - Intern

The Role
We are looking for exceptional builders to help develop AI systems that learn and improve from real-world feedback. You will work across LLMs, agentic workflows, evaluation systems, and production AI infrastructure, turning cutting-edge research into reliable products. Some weeks you'll be experimenting with new models and evaluation methods. Other weeks you'll build production features and collaborate closely with customers to solve real-world AI challenges.
What you'll do:

• Design and implement LLM-powered systems and scalable agentic workflows in production
• Work on open-ended problems in self-improving AI: agentic systems, auto-evals, verifier research, and benchmarks
• Build robust data processing pipelines for evaluation datasets and feedback loops
• Run experiments, iterate fast, and push ideas from hypothesis to working system
• Work closely with customers and the core team to deeply understand workflows and deliver meaningful impact
• Publish findings through technical blogs, research papers, or open artifacts that strengthen our technical foundation

What we look for:

• Currently pursuing a Bachelor's, Master's, or PhD in Computer Science, Machine Learning, Engineering, or a related field
• Hands-on experience building LLM-powered or agentic systems, in production or research settings
• Strong research taste, especially in evaluation design, post-training methods, and model improvement workflows
• Desire to own problems end-to-end, from first idea to shipped artifact
• Obsession with detail across research rigor, code quality, and clean modular design
• Comfortable working directly with a small, fast-moving team

Our Core Values:

• Customer Obsession - We start with the customer and work backwards. We aim to earn trust through consistent delivery, thoughtful listening, and by obsessing over customers.
• Intellectual Honesty - We operate with high trust and low ego. Ideas matter more than titles, and we communicate openly and directly while assuming good intent, even in strong disagreement.
• Bias for Action - We set high standards and move quickly to meet them. We prefer building and learning with customers over debating in the abstract, and we iterate based on real feedback.
• Extreme Ownership - We take responsibility for outcomes, not just tasks. Ownership means seeing problems through to completion and ensuring solutions truly work in practice.

In this role, you’ll work closely with the NeoSigma team. This role has a natural path towards full-time conversion.