Machine Learning Engineer (Relevance & Learning Systems)
Wizard
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About the role
Role Overview
As a Machine Learning Engineer (Relevance & Learning Systems) at Wizard, you will design and build feedback-driven learning systems that continuously improve an AI agent over time. You’ll connect live conversational interactions with real shopping behavior, turning user activity into actionable learning signals.
Key Missions
- Conceive and build learning systems that improve the AI agent over time using real feedback.
- Transform user interactions into learning signals, designing practical feedback loops and shipping systems that improve key product metrics.
- Build and industrialize feedback loops to enhance agent performance continuously.
Responsibilities
- Own signal pipelines end-to-end.
- Partner closely with product and engineering.
- Iterate quickly and deliver measurable improvements in core product outcomes.
Requirements
- Deep knowledge of Python and ML tooling.
- Experience shipping ML systems to production.
- Experience with recommendation systems, ranking, personalization, or optimization.
- Bachelor’s or Master’s degree in Computer Science.
- 5–8 years hands-on experience building and shipping ML systems.
Nice-to-haves / Additional Traits
- Pragmatic mindset: prefer simple, effective solutions over theoretically perfect ones.
About Wizard
Wizard builds AI-driven products, including a live conversational agent, and focuses on improving real-world outcomes through continuous learning systems. The company operates at the intersection of conversational AI and shopping behavior, using user interactions as signals to enhance agent performance over time.
Scraped 5/14/2026