Modelling Resident (AI)

TL;DR

Modelling Resident (AI): Developing adaptive algorithms and efficient intelligence with an accent on real-time learning and gradient-free exploration. Focus on cross-stack optimization and integrating product signals into model alignment.

Location: Global Remote (mention of New York, San Francisco, United States)

Company

A frontier lab focused on building efficient, adaptive intelligence that evolves in real-time to expand access and innovation.

What you will do

• Co-design adaptive algorithms that react in real-time to product signals and feedback.
• Explore new methods of capturing feedback to improve algorithmic performance.
• Collaborate across software, hardware, and algorithmic domains to drive system-wide efficiency.
• Develop and optimize models with a focus on real-world impact and technical excellence.
• Own outcomes end-to-end within a high-talent-density environment.

Requirements

• Degree or equivalent research/engineering experience in a computer science field.
• Project experience in model efficiency, synthetic data, interfaces, real-time alignment, or algorithmic optimization.
• Strong Python skills and experience with deep learning frameworks (PyTorch, JAX, or TensorFlow).
• Familiarity with model optimization techniques such as RLHF and fine-tuning.
• Systems thinking ability to optimize across the full ML stack.
• Strong communication skills for effective collaboration in a remote environment.

Culture & Benefits

• Direct mentorship from the core modelling team.
• Culture that values impact over credentials and encourages bold ideas.
• Environment focused on technical excellence and owning outcomes.
• Opportunity to build a strong professional track record in a frontier AI lab.