Research Engineer/Scientist - Human Alignment, Consumer Devices

Details

About the Team

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 a vision for the future of computing. The team works at the frontier of multimodal AI, turning emerging model capabilities into product experiences that are useful, delightful, and worthy of long-term trust.

Work explores 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 aligned with a person’s broader goals, values, and well-being. The team collaborates across research, engineering, design, product, and safety to build AI systems that know users over time, act at the right moment, and help in ways that are context-aware, respectful, and demonstrably beneficial.

About the Role

This role is for a Research Engineer / Scientist on the Future of Computing Research team to work on RLHF and post-training for personalized, multimodal AI systems. The focus is on building learning and evaluation foundations so models become more context-aware, adaptive, and useful over time. Problems include reward modeling, preference learning, long-horizon evaluation, and policy improvement for systems that must make high-quality behavioral decisions in realistic user settings. Work is product-grounded: success is measured by better model behavior in real-world use, not only benchmark performance.

This role is based in San Francisco, CA. The team uses a hybrid work model of four days in the office per week and offers relocation assistance to new employees.

Responsibilities

• 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 on whether behavior improves outcomes over time.
• Collaborate with safety researchers to ensure adaptation and personalization remain aligned, interpretable, and bounded by clear constraints.
• Prototype and iterate on training recipes, reward formulations, data pipelines, and evaluation suites for product-relevant behaviors.
• Help define how success is measured for personalized AI systems, including trust, appropriateness, and long-term user benefit.

Requirements

• Strong background in machine learning research with experience in RLHF, reward modeling, preference optimization, or post-training for large models.
• Experience in one or more of: reinforcement learning, ranking, recommender systems, personalization, memory, or human-in-the-loop evaluation.
• Experience designing clean experiments, reliable evaluations, and decision-useful metrics.
• Experience building datasets or evaluation pipelines grounded in human preferences, rubrics, or real-world product behavior.
• Comfortable working across the stack from data generation and labeling strategy to training runs, reward functions, and analysis.
• Interest in multimodal AI and in how models can learn from richer interaction signals over time.
• Willingness to work on product-shaping research with high stakes for trust, alignment, and long-term user value and to collaborate closely with engineers, designers, and safety researchers.

Benefits

• Base salary range: $380,000 - $445,000 (additional compensation includes equity and potential performance-related bonuses).
• Medical, dental, and vision insurance with employer contributions to Health Savings Accounts.
• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses.
• 401(k) retirement plan with employer match.
• Paid parental leave and paid medical/caregiver leave.
• Paid time off (flexible PTO for exempt employees; up to 15 days annually for non-exempt employees).
• 13+ paid company holidays and periodic company office closures.
• Mental health and wellness support; employer-paid basic life and disability coverage.
• Annual learning and development stipend.
• Daily meals in offices and meal delivery credits as eligible.
• Relocation support for eligible employees.
• Additional taxable fringe benefits (e.g., charitable donation matching, wellness stipends).

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. The company emphasizes safety and human needs in AI development and is an equal opportunity employer. Background checks will be administered consistent with applicable law. Reasonable accommodations for applicants with disabilities are available.