Staff/Principal Research Scientist

Inworld AI

. Conduct research on realtime AI for consumer-facing applications .

Posted 10/14/2026full-timeMountain View • California • United StatesLead💰 $270,000 - $500,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in foundation models, advanced AI architectures, and evaluation methodologies, with a strong focus on research ownership and collaboration in consumer-facing applications. Proven ability to conduct experiments, publish research, and contribute to interdisciplinary AI projects.

Highest-signal resume keywords

Foundation ModelsEvaluation MethodologiesMultimodal ModelsPublished ResearchPhD in ML/NLP

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Training Foundation ModelsReinforcement LearningReward ModelingQuality MeasurementEvaluation LoopsLarge-Scale Serving InfrastructureModular APIsExperiment DesignAI ArchitecturesTest-Time Compute

Soft Skills

Ability to Learn QuicklyThrive in Ambiguity

Industry Keywords

Consumer ApplicationsAI CapabilitiesHealthcareFitnessEducationMediaInterdisciplinary ExperimentsOpen-Source ContributionsResearch QuestionsShipped Results

About the role

Key responsibilities & impact

Conduct research on realtime AI for consumer-facing applications
Work on first-party speech models, LLM serving, realtime inference, large-scale serving infrastructure, and modular APIs
Frame unclear research questions and design experiments to answer them
Train and develop foundation models and advanced AI architectures
Build evaluation benchmarks, evaluation loops, and quality measurement systems
Research multimodal models, agents, tool use, test-time compute, and world models
Take full-stack ownership from research question through experiments, publications, and shipped results
Collaborate in person with the team in the Mountain View office
Contribute to AI capabilities supporting companions, healthcare, fitness, education, media, and other consumer applications

Requirements

What you’ll need

Experience with foundation models, including training, new architectures, reinforcement learning, reward modeling, and scaling
Experience with evaluation, including benchmarks, evaluation loops, quality measurement, LLM-as-judge, and failure analysis
Experience with frontier topics such as multimodal models, agents, tool use, test-time compute, and world models
Published research at ICML, ICLR, NeurIPS, EMNLP, ACL, or AAAI
PhD in ML/NLP or equivalent practical experience
Public work including non-trivial AI side projects, interdisciplinary experiments, or open-source contributions
Full-stack research ownership, from framing questions through experimentation, paper writing, and shipping results
Ability to learn quickly and thrive in ambiguity
Ability to work in person in the Mountain View office
Willingness to relocate to the San Francisco Bay Area if needed
Legal authorization to work in the United States

Benefits

Comp & perks

Bonus
Equity
Benefits
Relocation assistance
In-person collaboration and strong team culture
Support for sharing work that moves the field forward