Researcher at Inworld

Setup: Remote - Switzerland
Type: Full-time
Posted: Jan 17, 2026

Description

Inworld is seeking a researcher to join their team. The ideal candidate will have a background in foundation models, evaluation methods, and frontier topics in machine learning/natural language processing. Experience with published research at conferences like ICML, ICLR, NeurIPS, EMNLP, ACL, or AAAI is preferred. Candidates should possess strong analytical and communication skills, capable of driving impactful research outcomes.

Required Skills

Foundation Models
Reinforcement Learning
Reward Modeling
Scaling
Evaluation
Benchmarks
Eval Loops
Quality Measurement
LLM-as-Judge
Failure Analysis
Multimodal Models
Agents
Tool Use
Test-Time Compute
World Models
Published Research
ICML
ICLR
NeurIPS
EMNLP
ACL
AAAI
Public Work
Non-Trivial AI Side Projects
Interdisciplinary Experiments
Open-Source Contributions
Full-Stack Research Ownership
English Fluency

Additional Information

Preferred Qualifications: Experience in foundation models, including training, new architectures, reinforcement learning, reward modeling, and scaling.
Proficiency in evaluation methodologies such as benchmarking, evaluating loops, quality measurement, using large language models as judges, and failure analysis.
Knowledge of frontier topics like multimodal models, agent capabilities, tool usage, test-time computation, and world models.
Published research at prestigious conferences such as ICML, ICLR, NeurIPS, EMNLP, ACL, or AAAI.
Possession of a PhD in Machine Learning/Natural Language Processing or equivalent practical experience.
Engagement in public work, including non-trivial AI-side projects, interdisciplinary experiments, and open-source contributions.
Ability to own full-stack research, encompassing questioning framing, experimentation running, paper writing, and results deployment.
Fluency in English, both written and spoken, essential for collaboration with US-based leadership and engineering teams.