Modelling Resident

adaption; San Francisco (CA); Remote; USD 190,000 - 230,000; Full time

Job summary

adaption is seeking engineers to build adaptive algorithms that learn and respond to real-time product feedback. You will collaborate across software, hardware, and algorithms to push system-wide efficiency and real-world impact.

The role emphasizes strong Python skills, experience with DL frameworks, and remote collaboration. You will contribute to optimizing models and refining real-time alignment strategies for scalable AI systems.

Qualifications

• A degree or equivalent research/engineering experience in a computer science field.
• Genuine interest in at least one project touching: model efficiency, synthetic data, interfaces, real-time alignment, or algorithmic optimization.
• Systems thinking—ability to optimize across the full ML stack.
• Strong Python skills and 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—able to collaborate in a remote environment and accept feedback.
• You care about technical excellence and owning outcomes end to end.

Responsibilities

• Innovation: Build the future of adaptive algorithms that continuously learn and respond in real time to product signal and feedback.
• Cross-Stack Optimization: Collaborate across software, hardware, and algorithms to drive system-wide efficiency gains.
• Measure What Matters: Focus on real-world impact and the ability of the algorithm to interact with the world.

Skills

Python

DL frameworks

RLHF

System thinking

Communication

Remote collaboration

Real-time adaptability

Algorithm optimization

Bold ideation

Education

CS degree or equivalent

Tools

PyTorch

JAX

TensorFlow

Job description

The Role

Responsibilities

• Innovation: Build the future of adaptive algorithms that continuously learn. Co-design algorithms that react in real-time to product signal and feedback, and explore new ways of capturing feedback that make those algorithms better


• Cross-Stack Optimization: Collaborate across software, hardware, and algorithmic domains to drive system-wide efficiency gains


• Measure What Matters: We believe the ultimate signal of value is real-world impact. The smartest algorithm is one capable of interacting with the world - that's why product signal matters so much to how we work.

Qualifications

We value impact over credentials. Above all, we're looking for great teammates who make work feel lighter and aren't afraid to go out on a limb with bold ideas. You don't need to check every box - but you do need to be adaptable.

• A degree or equivalent research/engineering experience in a computer science field.


• Genuine interest in, and at least one project touching: model efficiency, synthetic data, interfaces, real-time alignment, or algorithmic optimization


• Systems thinking - the ability to understand and optimize across the full ML stack


• Strong Python skills and 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 - you know how to collaborate in a remote environment and you're open to feedback


• You care about technical excellence and last mile impact. We value impact more than effort, and about owning outcomes end to end.

About Us

Most AI is frozen in place - it doesn't adapt to the world. We think that's backwards. Our mandate is to build efficient intelligence that evolves in real-time. Our vision is AI systems that are flexible, personalized, and accessible to everyone. We believe efficiency is what makes this possible - it's how we expand access and ensure innovation benefits the many, not the few. We believe in talent density: bringing together the best and most driven individuals to push the boundaries of continual adaptation. We're looking for builders and creative thinkers ready to shape the next era of intelligence.