Role overview
Machine Learning Engineer - Agentic Systems
Location: Hybrid, San Francisco
Salary: Up to $250,000 + Equity
What you'll work on
- Design and build the core agentic platform that powers autonomous marketing agents end-to-end.
- Architect the foundational data and signal layer using a modern lakehouse approach, including robust pipelines and ML serving systems.
- Build reliable, safe “tool machines” that let agents interact with external systems and the real world.
- Develop customer-facing applications, such as a seamless chat UI where users collaborate with their AI partners.
- Collaborate with data scientists to build MLOps infrastructure for training, fine-tuning, and deploying state-of-the-art reasoning models.
What we're looking for
- 4+ years of experience in machine learning engineering, able to write production-grade code.
- Experience in either ML platform work (data, infra, serving, MLOps) or ML modelling (training, fine-tuning, evaluation) and ideally both.
- Product-minded engineer and systems-level thinker who can navigate ambiguity and design for scale, reliability, and extensibility.
- Comfortable working in an early-stage environment with high ownership, fast iteration, and 4-6 week R&D sprints.
- Excited about AI agents, performance marketing, and building systems that directly move measurable business metrics.
Tags & focus areas
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