Research Scientist (Test Time Compute)

Job DescriptionJob DescriptionAI Research Scientist (Test Time Compute) | naptha.ai About the role We are seeking an exceptional AI Research Scientist to join Naptha AI at the ground floor, focusing on advancing the state of the art in test time compute optimization for large models. In this role, you will be responsible for researching and developing novel approaches to improve inference efficiency, reduce computational requirements, and enhance model performance at deployment. Working directly with our technical team, you will help shape the fundamental architecture of our inference optimization platform. This role is critical in solving core technical challenges around model compression, efficient inference strategies, and deployment optimization. You will work at the intersection of machine learning, systems optimization, and hardware acceleration to develop practical solutions for real-world model deployment and scaling. Core

ResponsibilitiesResearch

& Development Design and implement novel architectures for efficient model inference

Develop frameworks for model compression and quantization

Research approaches to optimize test-time computation across different hardware

Create efficient protocols for distributed inference and resource management

Implement and test new ideas through rapid prototyping

Technical Innovation Stay at the forefront of developments in ML efficiency and inference optimization

Identify and solve key technical challenges in model deployment

Develop novel approaches to model compression and acceleration

Bridge theoretical research with practical implementation

Contribute to the academic community through publications and open source

Platform Development Help design and implement efficient inference pipelines

Develop scalable solutions for model deployment and serving

Create tools and frameworks for performance monitoring and optimization

Collaborate with engineering team on implementation

Build proofs of concept for new optimization techniques

Leadership & Collaboration Work closely with engineering team to implement research findings

Mentor team members on advanced optimization techniques

Contribute to technical strategy and roadmap

Collaborate with external research partners when appropriate

Help evaluate and integrate external research developments

In this role, you're a good fit if you have: Strong background in machine learning and systems optimization

Deep understanding of model compression and efficient inference techniques

Hands-on experience with modern ML frameworks and deployment tools

Experience with ML infrastructure and hardware acceleration

Track record of implementing efficient ML systems

Excellent programming skills (Python required, C++/CUDA a plus)

Strong analytical and problem-solving abilities

PhD in Machine Learning, Computer Science, Mathematics, or equivalent experience is a plus

Published research in relevant fields is a plus

Required Technical Experience: Python programming and ML frameworks (PyTorch, TensorFlow)

Experience with model optimization techniques (quantization, pruning, distillation)

MLOps and efficient model deployment

Hardware acceleration (GPU, TPU optimization)

Version control and collaborative development

Experience with large models

About the hiring process: Initial technical interview

Research presentation

System design discussion

Technical challenge

Team collaboration interview

Compensation & Benefits: Competitive salary with significant equity stake

Remote-first work environment

Full medical, dental, and vision coverage

Flexible PTO policy

Learning and development budget

Conference and research publication support

Home office setup allowance

Additional Notes: Must be comfortable with ambiguity and rapid iteration typical of pre-seed startups

Strong bias for practical implementation of research ideas

Passion for advancing the field of efficient ML systems

Interest in open source contribution and community engagement

Naptha AI is committed to building a diverse and inclusive workplace. We are an equal opportunity employer and welcome applications from all qualified candidates regardless of background.

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