Modelling Resident

The role

You will build adaptive algorithms that continuously learn and co-design algorithms that react in real-time to product signal. You will collaborate across software, hardware, and algorithmic domains to drive system-wide efficiency gains.

What you will do

• Build the future of adaptive algorithms that continuously learn
• Co-design algorithms that react in real-time to product signal and feedback
• Explore new ways of capturing feedback to improve algorithms
• Collaborate across software, hardware, and algorithmic domains to drive system-wide efficiency gains
• Measure real-world impact

Required qualifications

• A degree or equivalent research/engineering experience in a computer science field
• At least one project touching model efficiency, synthetic data, interfaces, real-time alignment, or algorithmic optimization
• Systems thinking to understand and optimize across the full ML stack
• Strong Python skills
• Experience with deep learning frameworks (PyTorch, JAX, or TensorFlow)
• Familiarity with model optimization techniques such as RLHF and fine-tuning
• Strong communication and self-awareness
• Ability to collaborate in a remote environment

Nice to have

• Genuine interest in model efficiency, synthetic data, interfaces, real-time alignment, or algorithmic optimization

Benefits

• Adaption Passport: an annual travel allowance to explore somewhere new
• Weekly allowance for takeout or grocery delivery
• High-quality medical coverage and benefits
• Team offsites and visits to SF HQ

About the company

adaption builds efficient intelligence that evolves in real-time. The team is small, talent-dense, and operates with high velocity and extreme ownership.