At Scale, our mission is to accelerate the development of AI applications. We're looking for a Machine Learning Research Scientist/Engineer to join our team and help us shape the future of AI.

This role operates at the forefront of AI research and real-world implementation, with a strong focus on reasoning within large language models (LLMs). You will study the data types critical for advancing LLM-based agents, including browser and software engineering (SWE) agents. You will play a key role in shaping Scale's data strategy by identifying the most effective data sources and methodologies for improving LLM reasoning.

Success in this role requires a deep understanding of LLMs, planning algorithms, and novel approaches to agentic reasoning, as well as creativity in tackling challenges related to data generation, model interaction, and evaluation. You will contribute to impactful research on language model reasoning, collaborate with external researchers, and work closely with engineering teams to bring state-of-the-art advancements into scalable, real-world solutions.

Responsibilities

• Study the data types critical for advancing LLM-based agents, including browser and software engineering (SWE) agents
• Shape Scale's data strategy by identifying the most effective data sources and methodologies for improving LLM reasoning
• Contribute to impactful research on language model reasoning
• Collaborate with external researchers
• Work closely with engineering teams to bring state-of-the-art advancements into scalable, real-world solutions

Requirements

• Practical experience working with LLMs, with proficiency in frameworks like PyTorch, JAX, or TensorFlow
• A track record of published research in top ML and NLP venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, CoLLM, etc.)
• At least three years of experience solving complex ML challenges, either in a research setting or product development, particularly in areas related to LLM capabilities and reasoning
• Strong written and verbal communication skills, along with the ability to work effectively across teams

Nice to Have

• Hands-on experience fine-tuning open-source LLMs or leading bespoke LLM fine-tuning projects using PyTorch/JAX
• Research and practical experience in building applications and evaluations related to LLM-based agents, including tool-use, text-to-SQL, browser agents, coding agents, and GUI agents
• Experience with agent frameworks such as OpenHands, Swarm, LangGraph, or similar
• Familiarity with advanced agentic reasoning techniques such as STaR and PLANSEARCH
• Proficiency in cloud-based ML development, with experience in AWS or GCP environments

Benefits

• Comprehensive health, dental and vision coverage
• Retirement benefits
• A learning and development stipend
• Generous PTO
• Commuter stipend

Salary Range

$252,000-$315,000 USD

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About the Team

OpenAI’s mission is to ensure that artificial general intelligence (AGI) benefits all of humanity. A key part of achieving that mission is training models that deeply understand and reflect human preferences — the Human Data team is at the heart of that effort.

The Human Data engineering team creates the systems that enable scalable, high-quality human feedback. These systems are essential to how OpenAI trains and improves its most advanced models. Engineers on this team collaborate closely with world-class researchers to bring alignment techniques to life — from experimental ideas to production-ready feedback loops.

About the Role

We’re looking for software engineers to join the Human Data team and build the platforms, prototypes, tools, and infrastructure that power how our AI models are trained, aligned, and evaluated. You’ll partner with researchers and cross-functional teams to bring alignment ideas to life, influence future model training, and shape how models interact with the real world.

We’re looking for people who are excited by technical ownership, enjoy working across the stack, and are eager to solve ambiguous problems in a high-impact, fast-paced environment.

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:

• Build and maintain robust full-stack systems for feedback collection, data labeling, and evaluation pipelines, while maintaining high levels of security.

• Translate experimental alignment research into scalable production infrastructure, including inference and model training stacks.

• Design and iterate on user-facing tools and backend services to support high-quality data workflows

• Partner with researchers, engineers, and program leads to shape feedback loops and model interaction paradigms

• Drive infrastructure improvements that enable faster iteration and scaling across OpenAI’s frontier models, from internal research tooling all the way to production ChatGPT.

You might thrive in this role if you:

• Have strong software engineering fundamentals and experience building production systems at scale

• Enjoy full-stack development with end-to-end ownership — from backend pipelines to user interfaces

• Are motivated by high-impact collaboration with research teams and solving novel, ambiguous problems

• Are excited to shape how AI systems learn from human preferences and reflect a broad range of human values

• Care deeply about inclusive tooling and building systems that enhance model safety, reliability, and usefulness

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.

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