Research Scientist (Test Time Compute)

Join to apply for the Research Scientist (Test Time Compute) role at Naptha AIJoin to apply for the Research Scientist (Test Time Compute) role at Naptha AIGet AI-powered advice on this job and more exclusive features.AI Research Scientist (Test Time Compute) | naptha.aiAbout The RoleWe 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 language 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 & DevelopmentDesign and implement novel architectures for efficient model inferenceDevelop frameworks for model compression and quantizationResearch approaches to optimize test-time computation across different hardwareCreate efficient protocols for distributed inference and resource managementImplement and test new ideas through rapid prototypingTechnical InnovationStay at the forefront of developments in ML efficiency and inference optimizationIdentify and solve key technical challenges in model deploymentDevelop novel approaches to model compression and accelerationBridge theoretical research with practical implementationContribute to the academic community through publications and open sourcePlatform DevelopmentHelp design and implement efficient inference pipelinesDevelop scalable solutions for model deployment and servingCreate tools and frameworks for performance monitoring and optimizationCollaborate with engineering team on implementationBuild proofs of concept for new optimization techniquesLeadership & CollaborationWork closely with engineering team to implement research findingsMentor team members on advanced optimization techniquesContribute to technical strategy and roadmapCollaborate with external research partners when appropriateHelp evaluate and integrate external research developmentsIn this role, you're a good fit if you have:Strong background in machine learning and systems optimizationDeep understanding of model compression and efficient inference techniquesHands-on experience with modern ML frameworks and deployment toolsExperience with ML infrastructure and hardware accelerationTrack record of implementing efficient ML systemsExcellent programming skills (Python required, C++/CUDA a plus)Strong analytical and problem-solving abilitiesPhD in Machine Learning, Computer Science, Mathematics, or equivalent experience is a plusPublished research in relevant fields is a plusRequired Technical Experience:Python programming and ML frameworks (PyTorch, TensorFlow)Experience with model optimization techniques (quantization, pruning, distillation)MLOps and efficient model deploymentHardware acceleration (GPU, TPU optimization)Version control and collaborative developmentExperience with large language modelsAbout the hiring process:Initial technical interviewResearch presentationSystem design discussionTechnical challengeTeam collaboration interviewCompensation & Benefits:Competitive salary with significant equity stakeRemote-first work environmentFull medical, dental, and vision coverageFlexible PTO policyLearning and development budgetConference and research publication supportHome office setup allowanceAdditional Notes:Must be comfortable with ambiguity and rapid iteration typical of pre-seed startupsStrong bias for practical implementation of research ideasPassion for advancing the field of efficient ML systemsInterest in open source contribution and community engagementNaptha AI is committed to building a diverse and inclusive workplace. 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Created: 2025-09-17