Engineering Manager, AgentOps
Scale AI · San Francisco, CA | New York City, NY · Enterprise Engineering
About this role
Scale AI is hiring a manager-level Engineering Manager in the software engineering function based in San Francisco, CA | New York City, NY. The posting calls out experience with LLMs, Reinforcement Learning, System Design, Full Stack. Compensation is listed at $252,000–$315,000 per year.
- Role
- Engineering Manager
- Function
- software engineering
- Level
- manager
- Track
- hybrid
- Employment
- Full-time
- Location
- San Francisco, CA | New York City, NY
- Department
- Enterprise Engineering
More roles at Scale AI
Job description
from Scale AI careersAt 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 recent 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 Data Engine
Our Generative AI Data Engine powers the world’s most advanced LLMs and generative models through world-class RLHF (Reinforcement Learning with Human Feedback), human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI.
About our AgentOps team:
The vision for the AgentOps team is to build the best Agent Development Platform in the AI Industry.
Agent Development is in its nascent stages in a rapidly changing industry, with limited tooling making it hard for agent developers to manage agent lifecycles. As a team that has a front-row seat to what Enterprise customers need and want, we want to build an opinionated but flexible platform for all Agent operations ("AgentOps"), including building, deploying, monitoring, evaluating and improving agents to solve customer needs.