Job Details

About Scale

At Scale, 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 recent Series F round, we're accelerating the development of autonomous AI agents in frontier labs through agentic data and evaluations, paving the road to Artificial General Intelligence (AGI).

About the Autonomous Agents Team

The Autonomous Agents Team (A2) is a small team of customer-facing ML practitioners within Scale's Research organization dedicated to rapidly developing innovative agentic applications, tools, and data pipelines. Specializing in autonomous agents, the A2 team bridges deep generative AI and ML expertise with practical AI application development to create foundational agentic frameworks and tooling that supports our agent data programs, evaluations, and more. Our focus is on fully autonomous agents that dynamically complete tasks by interacting with external environments, such as code repositories, browsers, computer interfaces, and the real world using custom tools and actions.

About the Role

As an Applied AI Engineer on the Autonomous Agents team, you will be pivotal in bridging the gap between the rapidly evolving space of agent applications and frameworks, agentic LLM capabilities, and the data required to advance them.

You will:

• Design agent data programs that improve model performance through supervised fine-tuning (SFT) and reinforcement learning (RL)
• Build new agent data types and pipelines that enable agentic data collection using multiple environments, like code repos, browsers, and computers
• Meet regularly with customers to understand their modeling requirements and product objectives
• Develop agentic frameworks, tools, and verifiers to evaluate model capabilities for frontier general agent tasks
• Implement popular open source agent libraries and benchmarks on proprietary datasets and models
• Build agent applications that enable and automate key aspects of our data pipelines and evaluations

Ideally you'd have:

• A love for solving deeply complex technical problems with ambiguity using state of the art research and AI to build solutions
• Strong AI & engineering background: Master's degree/or equivalent experience in Computer Science, Machine Learning, AI, or a related field
• Strong background in deep learning, LLM, and data-centric AI methodologies
• 2-3 years of practical experience building AI applications for real-world use cases.
• Previous experience in a customer facing role
• Proficiency in Python to write, test and debug code using common libraries (ie numpy, pandas)

Nice to haves:

• Experience building AI applications on the modern GenAI stack, using commercial or open-source LLMs and common SDKs like the OpenAI API
• Experience building agents that use tools, generate structured output, and interact with environments
• Familiarity with agent data and benchmarks, such as SWE-Bench for SWE agents, and OS-World for Computer-use agents.

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