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Scale AI is looking to accelerate the development of AI applications, specifically focusing on studying data types essential for building state-of-the-art agents like browser and SWE agents. The goal is to advance intelligent, adaptable AI agents and guide the data strategy to drive innovation in this area.

Requirements

• Practical experience working with LLMs
• Proficiency in frameworks like Pytorch, Jax, or Tensorflow
• 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 sophisticated ML problems, either in a research setting or product development
• Hands-on experience with open source LLM fine-tuning or involvement in bespoke LLM fine-tuning projects using Pytorch/Jax
• Hands-on experience and publications in building applications and evaluations related to AI agents such as tool-use, text2SQL, browser agents, coding agents and GUI agents
• Hands-on experience with agent frameworks such as OpenHands, Swarm, LangGraph, etc.

Responsibilities

• Explore the data landscape needed to advance intelligent, adaptable AI agents
• Guide the data strategy at Scale to drive innovation
• Contribute to impactful research publications on agents
• Collaborate with customer researchers
• Work alongside the engineering team to translate these advancements into real-world, scalable solutions
• Interpret research literature and quickly turn new ideas into prototypes
• Address novel challenges related to data, interaction, and evaluation

Other

• Strong written and verbal communication skills
• Ability to operate cross-functionally
• Familiarity with agentic reasoning methods such as STaR and PLANSEARCH
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.