Deep Research Agent Tech Lead

Scale AI Scale AI · Data AI · New York, NY +1 · Enterprise Engineering

Scale AI is looking for a Staff/Senior Staff ML Engineer to lead Deep Research Agent Development for enterprise applications. This role involves setting technical strategy, driving research to production, and leading a team in building, orchestrating, and evaluating multi-agent systems at scale. Requires strong experience in Generative AI, LLMs, and AI Agents, with a focus on integrating diverse data modalities and ensuring production-readiness.

What you'd actually do

  1. Define and own the technical strategy, architecture, and roadmap for Deep Research Agents for the Enterprise, ensuring alignment with Scale AI’s overall AI strategy and business goals.
  2. Lead the end-to-end development, from initial research to production deployment, to landing on customer impact, with a focus on integrating diverse data modalities.
  3. Design and champion highly scalable, reliable, and low-latency infrastructure and frameworks for building, orchestrating, and evaluating multi-agent systems at enterprise scale.
  4. Serve as the technical authority for the team, leading design reviews, defining ML engineering best practices, and ensuring code quality, security, and operational excellence for all agent systems.
  5. Technically lead and mentor a team of Machine Learning Engineers and Research Scientists, fostering a culture of innovation, rigorous engineering, rapid iteration, and technical depth.

Skills

Required

  • Machine Learning
  • Deep Learning
  • Applied Research
  • Generative AI
  • Large Language Models (LLMs)
  • AI Agents
  • Agentic systems
  • large-scale distributed systems
  • real-time data processing
  • Technical Leadership

Nice to have

  • Master's or Ph.D.
  • Text-to-SQL systems
  • Multimodal AI
  • OCR
  • vision-language models
  • document intelligence
  • Reinforcement Learning (RL)
  • Reasoning and Planning
  • vector databases
  • research papers in top-tier ML/AI conferences
  • cross-team technical initiatives

What the JD emphasized

  • Deep Research Agent Development
  • Generative AI
  • Large Language Models (LLMs)
  • Agentic Frameworks
  • AI Agents
  • Agentic systems
  • multi-agent systems

Other signals

  • Deep Research Agent Development
  • Generative AI
  • Large Language Models (LLMs)
  • Agentic Frameworks
  • multi-agent systems