Machine Learning Engineer
One of the first ML Engineers at a 25-person rocketship automating a $1T industry. Design and build the entire ecosystem where autonomous AI agents live, learn, and operate — with greenfield scope across the full stack.
Autonomous AI Agents for a $1T Market
Our client was founded by technologists and operators who spent over a decade building ad platforms and e-commerce engines. They are pioneering autonomous growth agents that bring advanced data science and machine learning to every business — targeting a $1T global performance marketing industry.
A rapidly growing network of D2C brands rely on their intelligent agents to simplify marketing complexity, uncover actionable insights, and autonomously drive measurable results. Customers are already seeing a 40% performance lift.
World-class advisor — former President/GM at a top global technology company, with direct experience building one of the largest digital advertising platforms in the world.
What You’ll Build
As one of the first ML Engineers at the company, you’ll be an architect of the entire ecosystem where AI agents live, learn, and operate. Greenfield scope. Outsized impact across the full stack.
- Design and build the core agentic platform — the engine that allows the company to craft, manage, and continuously improve autonomous agents
- Architect the foundational data and signal platform using a modern lakehouse architecture with robust pipelines and ML serving systems
- Build a suite of powerful, reliable, and safe tool integrations that allow agents to interact with the world
- Develop customer-facing applications including a chat UI where users collaborate with AI agents
- Build MLOps infrastructure for training, fine-tuning, and deploying state-of-the-art reasoning models in collaboration with data scientists
Stack & Tools
What They’re Looking For
- Background at well-known technology companies — Big Tech or highly reputable startups — ideally in ads, search, or recommendation systems. Best fit is Big Tech + startup combination (top Big Tech companies in ads/search ideal)
- Hands-on ML modeling and training experience — not just infrastructure
- Master’s or PhD in CS, or Bachelor’s + 2+ years professional software engineering
- Production-level Python code proficiency
- Ability to work from the Mountain View, CA office (hybrid available for SF-based candidates)
- 3–8 years of ML engineering experience with production-level code (ML platform or modeling background both acceptable)
- Hands-on experience with LLMs, agentic frameworks (e.g. LangGraph), or RAG systems
- Experience with ML frameworks (PyTorch, TensorFlow) or MLOps infrastructure (MLflow, Kubernetes, serving systems)
- Product-minded with a strong focus on end-user experience
- Prior experience at a high-growth, venture-backed startup
- Degree from a Top 30 university or equivalent tier-1 company experience
- Data engineering experience — ETL/streaming pipelines, Spark, Airflow, dbt, or lakehouse architecture
Interview Process
Completable within 2 weeks. Flexibility available for senior candidates.
Recruiter Call
Introduction and role alignment
CodeSignal Assessment
Technical coding evaluation
Onsite Interview
System design, ML depth, and cultural fit
Decision & Offer
Final decision and offer stage