Research Engineer​/Scientist - Human Alignment, Consumer Devices

Research Engineer / Scientist

The Future of Computing Research team is an applied research team within the Consumer Devices group focused on developing new methods, models, and evaluation frameworks that support our vision for the future of computing. We work at the frontier of multimodal AI, helping turn emerging model capabilities into product experiences that are useful, delightful, and worthy of long-term trust.

Our work explores a new class of AI systems that can learn over time, adapt to individuals, and support people in the flow of daily life. This includes long-term memory, user modeling, and personalization systems that are aligned not just with immediate satisfaction, but with a person's broader goals, values, and well-being.

We work closely across research, engineering, design, product, and safety to define what it means to build AI systems that know you over time, act at the right moment, and help in ways that are context-aware, respectful, and demonstrably beneficial.

This role is based in San Francisco, CA. We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees.

In this role, you will:

• Develop RLHF and post-training methods for multimodal models.
• Build reward models and preference-learning pipelines for adaptive, personalized model behavior.
• Design datasets, rubrics, and evaluation frameworks that capture user preferences, contextual appropriateness, and long-term value in realistic tasks.
• Run experiments on policy improvement using explicit feedback, implicit signals, and model-based grading.
• Work on long-horizon evaluation problems, where model quality depends not just on a single response but on whether behavior improves outcomes over time.
• Collaborate closely with safety researchers to ensure that adaptation and personalization remain aligned, interpretable, and bounded by clear constraints.
• Prototype and iterate quickly on training recipes, reward formulations, data pipelines, and evaluation suites for product-relevant behaviors.
• Help define how OpenAI measures success for personalized AI systems including trust, appropriateness, and long-term user benefit.

You might thrive in this role if you:

• Have a strong background in machine learning research, with experience in RLHF, reward modeling, preference optimization, or post-training for large models.
• Have worked on one or more of: reinforcement learning, ranking, recommender systems, personalization, memory, or human-in-the-loop evaluation.
• Care about rigorous empirical work and know how to design clean experiments, reliable evals, and decision-useful metrics.
• Are excited by the challenge of training models against nuanced behavioral objectives.
• Have experience building datasets or eval pipelines grounded in human preferences, rubrics, or real-world product behavior.
• Are comfortable working across the stack, from data generation and labeling strategy to training runs, reward functions, and analysis.
• Are interested in multimodal AI and in how models can learn from richer interaction signals over time.
• Want to work on product-shaping research with unusually high stakes for trust, alignment, and long-term user value.
• Enjoy close collaboration with engineers, designers, and safety researchers to turn frontier research into real systems.

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.

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.

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