リサーチャー, マルチモーダルセーフティ
研究員正社員—サンフランシスコハイブリッド
マルチモーダルモデルの安全性を研究し、トレーニングや評価手法を開発します。テキスト、視覚、音声データを活用し、モデルの安全な挙動を導くための研究を行います。ハイブリッド勤務モデルを採用しており、週3日のオフィス出社が必要です。研究およびエンジニアリングの判断力を活かし、仮説の立案や実験設計を担当します。
マルチモーダルモデルの安全性を研究し、トレーニングや評価手法を開発します。テキスト、視覚、音声データを活用し、モデルの安全な挙動を導くための研究を行います。ハイブリッド勤務モデルを採用しており、週3日のオフィス出社が必要です。研究およびエンジニアリングの判断力を活かし、仮説の立案や実験設計を担当します。
OpenAI is at the center of some of the highest-impact multimodal work in AI. ChatGPT serves a massive global audience, and enables diverse interactions via text, speech, and visuals. As interactive surfaces grow, models also need to adapt to emerging harm, understand user intent and situational context, and respond appropriately.
The Chat and Multimodal Safety team is responsible for ensuring that OpenAI’s increasingly multimodal models and products behave safely across these experiences. We develop the research, training methods, and evaluations needed to make these experiences safe. Our work sits at the frontier of responsibly deploying powerful AI, in close partnership with Personal AGI, io, model training, and product teams.
As a Researcher on the Chat and Multimodal Safety team, you will help shape how frontier models perceive and reason the world, and translate that understanding into safe behavior.
We’re looking for people who combine deep technical expertise with strong safety judgment. Strong candidates often bridge perception and language: they may have built vision-language models, worked on modality fusion or image encoders, developed multimodal post-training or evaluations, or advanced safety for image, video, or audio systems.
This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
Define and advance multimodal safety research for text, vision, and audio, connecting perception and semantic understanding to safe model behavior.
Build training and evaluation methods for VLMs, including post-training, safety evals, and interventions that help models respond safely and appropriately in varied contexts.
Collaborate closely with Personal AGI, Consumer Devices, and product/model teams to translate research into safer ambient, embedded, and personalized multimodal experiences.
Have a track record of building or advancing multimodal models, with depth in vision-language models, video understanding, image generation, audio, or multimodal reasoning—and fluency across both perception and language.
Understand how multimodal systems work end to end, from encoders, projection layers, and modality fusion to cross-modal reasoning, scaling, and inference tradeoffs.
Have improved frontier model behavior through post-training, using approaches such as SFT, RL, data curation, synthetic data, evaluation, and rigorous error analysis.
Bring strong research and engineering judgment to open-ended safety problems: you can form testable hypotheses, design decisive experiments and evaluations, diagnose model failures, and translate findings into robust improvements.
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
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