Research Engineer/Research Scientist - Personal AGI, North Stars

About the Team

The Personal AGI team seeks to empower all of humanity to benefit from frontier intelligence in whatever way they choose. We are responsible for training models to deploy to millions of users globally via ChatGPT, the API, and future products. We aim to evolve ChatGPT from a chatbot to an infinitely capable and personalized superassistant supporting human flourishing.

We work on defining, measuring, and improving capabilities across the training stack. Our focus areas include but are not limited to model behavior, personalization, safety, factuality, instruction following, personality, interactivity, multilingual fluency, world interaction, and bringing agents to everyone. We chart the course for what to strive towards.

We partner closely with research and product teams across the company ensuring that our models are safe, efficient, and reliable.

About the Role

You’ll work as a Research Engineer / Scientist on the North Stars team within the broader Personal AGI research org. You will work on bringing the next generation of AI-enabled experiences to all of humanity by closing the capability overhang between power users and the average consumer, including areas like tool-use, feature discovery, connectors, and instruction following. You will think deeply about the current bottlenecks in model behavior, translate these insights into robust evals, training data, reward signals, and model and harness improvements.

We're looking for individuals with strong ML engineering skills and research experience passionate about creative, product-driven research.

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.

In this role, you will

• Own and pursue a research agenda to improve model capability and performance.

• Collaborate closely with the other research and product teams, allowing customers to optimize their own models.

• Build robust evaluations for tracking modeling improvements.

• Design, implement, test, and debug code across our research stack.

You might thrive in this role if you

• Have a deep understanding of machine learning and machine learning applications.

• Have a working knowledge of relevant models, and building evaluations for model capability improvement.

• Are comfortable diving into a large ML codebase to debug.

• Thrive in a dynamic and technically complex environment.

About OpenAI

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 https://cdn.openai.com/policies/eeo-policy-statement.pdf.

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 resultin

Responsibilities

• Own and pursue a research agenda to improve model capability and performance
• Collaborate closely with research and product teams to allow customers to optimize their own models
• Build robust evaluations for tracking modeling improvements
• Design, implement, test, and debug code across the research stack
• Work on defining, measuring, and improving capabilities across the training stack including model behavior, personalization, safety, factuality, instruction following, personality, interactivity, multilingual fluency, and world interaction
• Think deeply about bottlenecks in model behavior and translate insights into robust evals, training data, reward signals, and model improvements

Requirements

• Deep understanding of machine learning and machine learning applications
• Working knowledge of relevant models and building evaluations for model capability improvement
• Comfortable diving into a large ML codebase to debug
• Strong ML engineering skills and research experience

Preferred Qualifications

• Thrive in dynamic and technically complex environments
• Passionate about creative, product-driven research

• Hybrid work model of 3 days in the office per week
• Relocation assistance to new employees