Deep Research Agent Tech Lead
Scale AI · San Francisco, CA | New York City, NY · Enterprise Engineering
About this role
Scale AI is hiring a senior-level Technical Lead in the software engineering function based in San Francisco, CA | New York City, NY. The posting calls out experience with SQL, LLMs, Deep Learning, Reinforcement Learning. Compensation is listed at $264,800–$331,000 per year.
- Role
- Technical Lead
- Function
- software engineering
- Level
- senior
- Track
- Tech leadership
- Employment
- Full-time
- Location
- San Francisco, CA | New York City, NY
- Department
- Enterprise Engineering
More roles at Scale AI
Job description
from Scale AI careersScale AI is seeking a highly technical and strategic Staff / Senior Staff Machine Learning Engineer to act as the Tech Lead (TL) for our next generation of deep research agents for the Enterprise. This high-impact role will drive the technical direction and oversight for Deep Research Agent Development, translating cutting-edge research in Generative AI, Large Language Models (LLMs), and Agentic Frameworks into robust, scalable, and high-impact production systems that enhance enterprise operations, analytics, and core efficiency.
The ideal candidate thrives in a fast-paced environment, has a passion for both deep technical work and mentoring, and is capable of setting a long-term technical strategy for a critical domain while maintaining a strong, hands-on delivery focus.
Responsibilities
Technical Leadership & Vision
- Set the Technical Roadmap: 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.
- Drive Breakthrough Research to Production: 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.
- Core Agent Capabilities Development:
- Advanced Knowledge Retrieval: Architect and implement state-of-the-art retrieval systems to ensure the agents provide accurate and comprehensive answers from public and proprietary data sources from enterprises.