Scale AI
Machine Learning Research Scientist/ Engineer, Agents
Scale AI, New York, New York, us, 10261
Overview
Machine Learning Research Scientist/ Engineer, Agents at Scale AI. This role sits at the intersection of cutting-edge AI research and practical application, focusing on data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guide Scale's data strategy, and translate research into scalable, real-world solutions. About Scale
At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations. About The ACE Team
The Agent Capabilities & Environments (ACE) team, part of Scale’s Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more. About This Role
This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate these advancements into real-world, scalable solutions. Responsibilities
Study data critical for building state-of-the-art AI agents (e.g., browser and SWE agents) and define data strategies to enable scalable research and deployment. Collaborate with researchers and engineers to translate research findings into practical, scalable systems. Publish research results in top venues and contribute to internal and external knowledge sharing. Work with customer researchers and cross-functional stakeholders to shape data programs and evaluation methodologies. Qualifications
Practical experience with LLMs and proficiency in frameworks such as PyTorch, JAX, or TensorFlow; ability to interpret literature and rapidly prototype. A track record of published research in top ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, COLM, etc.). At least three years of experience addressing advanced ML problems in research or product development. Strong written and verbal communication skills and the ability to work cross-functionally. Nice to have
Hands-on experience with open-source LLM fine-tuning using PyTorch/JAX. Publications and hands-on work building AI agent applications (tool-use, text2SQL, browser agents, coding agents, GUI agents). Experience with agent frameworks (OpenHands, Swarm, LangGraph, etc.). Familiarity with agentic reasoning methods (e.g., STaR, PLANSEARCH). Experience with cloud stacks (AWS or GCP) and ML development in cloud environments. Compensation and Benefits
Compensation packages include base salary, equity, and benefits. The base salary range for this full-time position in San Francisco, New York, and Seattle is $220,000–$325,000 USD. The final offer is determined by location, skills, experience, and interview performance. Eligible Scale employees also receive equity-based compensation, subject to Board approval. Your recruiter can share the specific salary range for your location during the hiring process and confirm equity eligibility. Benefits typically include comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additional benefits such as commuter stipends may be available. Pay transparency and privacy
Note:
Our policy requires a 90-day waiting period before reconsidering candidates for the same role to ensure a fair evaluation process. We also comply with the U.S. Department of Labor's Pay Transparency provisions. We collect, retain, and use personal data for recruiting purposes in accordance with our privacy policy. The base salary range displayed on the job posting for certain locations is provided for transparency. Equal Opportunity
Scale is an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity, or Veteran status. We provide reasonable accommodations for applicants with disabilities. If you need assistance, please contact accommodations@scale.com.
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Machine Learning Research Scientist/ Engineer, Agents at Scale AI. This role sits at the intersection of cutting-edge AI research and practical application, focusing on data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guide Scale's data strategy, and translate research into scalable, real-world solutions. About Scale
At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations. About The ACE Team
The Agent Capabilities & Environments (ACE) team, part of Scale’s Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more. About This Role
This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate these advancements into real-world, scalable solutions. Responsibilities
Study data critical for building state-of-the-art AI agents (e.g., browser and SWE agents) and define data strategies to enable scalable research and deployment. Collaborate with researchers and engineers to translate research findings into practical, scalable systems. Publish research results in top venues and contribute to internal and external knowledge sharing. Work with customer researchers and cross-functional stakeholders to shape data programs and evaluation methodologies. Qualifications
Practical experience with LLMs and proficiency in frameworks such as PyTorch, JAX, or TensorFlow; ability to interpret literature and rapidly prototype. A track record of published research in top ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, COLM, etc.). At least three years of experience addressing advanced ML problems in research or product development. Strong written and verbal communication skills and the ability to work cross-functionally. Nice to have
Hands-on experience with open-source LLM fine-tuning using PyTorch/JAX. Publications and hands-on work building AI agent applications (tool-use, text2SQL, browser agents, coding agents, GUI agents). Experience with agent frameworks (OpenHands, Swarm, LangGraph, etc.). Familiarity with agentic reasoning methods (e.g., STaR, PLANSEARCH). Experience with cloud stacks (AWS or GCP) and ML development in cloud environments. Compensation and Benefits
Compensation packages include base salary, equity, and benefits. The base salary range for this full-time position in San Francisco, New York, and Seattle is $220,000–$325,000 USD. The final offer is determined by location, skills, experience, and interview performance. Eligible Scale employees also receive equity-based compensation, subject to Board approval. Your recruiter can share the specific salary range for your location during the hiring process and confirm equity eligibility. Benefits typically include comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additional benefits such as commuter stipends may be available. Pay transparency and privacy
Note:
Our policy requires a 90-day waiting period before reconsidering candidates for the same role to ensure a fair evaluation process. We also comply with the U.S. Department of Labor's Pay Transparency provisions. We collect, retain, and use personal data for recruiting purposes in accordance with our privacy policy. The base salary range displayed on the job posting for certain locations is provided for transparency. Equal Opportunity
Scale is an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity, or Veteran status. We provide reasonable accommodations for applicants with disabilities. If you need assistance, please contact accommodations@scale.com.
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