Machine Learning Engineer

Machine Learning Engineer - Agentic Systems

Location: Hybrid, San Francisco

Salary: Up to $250,000 + Equity

Industry: AI Agents / Performance Marketing / Data Platforms

Who You’ll Join:

Join an early-stage, fast-growing AI startup building autonomous agents to run performance marketing for small and mid-sized businesses, giving them “enterprise-grade” growth tech without big in-house teams. A fast-growing network of D2C brands and apps already relies on these agents for a 40% lift in performance, with 50+ customers and a growing waitlist.

The company recently raised a $25M seed round led by Kleiner Perkins, positioning it in the top 1% of seed-stage AI companies, and is going after a massive $1T ads market. You’ll be part of a ~27-person, high-density team with hands-on advisors like Jerry Dischler, the former Google executive who built the early Google Ads business.

What You’ll Do:

• 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.

Who You Are:

• 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.

Tech Stack:

Python, PyTorch, TensorFlow, LangGraph, Kubernetes, MLflow, Spark, Airflow, dbt

Why You’ll Thrive:

• Build the core agentic and data platform that directly controls millions in ad spend for SMBs and growth-stage brands.
• Join a $25M seed-stage company backed by Kleiner Perkins and other top-tier investors, with strong signal and runway.
• Work in a small, stellar team where talent density is high, and advisors include leaders like Jerry Dischler, who built Google Ads.
• See clear, quantifiable impact from your work, with customers already seeing around 40% lift and a growing client waitlist.
• Enjoy a hybrid setup centered in Mountain View, with flexibility for SF-based candidates and a culture that values good humans as much as strong engineers.

This role is open to US citizens, Green Card holders, and TN visa holders only.