Machine Learning Engineer - Relevance & Learning Systems

Wizard AI is a leading AI Shopping Agent focused on delivering accurate and trustworthy product recommendations. They are seeking a Machine Learning Engineer to design and build feedback-driven learning systems that enhance their AI agent's performance over time, leveraging user interactions to create effective learning signals.

Responsibilities:

• Build and productionize feedback loops that improve agent performance over time
• Build the evaluation infrastructure – offline metrics, regression suites, and experiment analysis
• Own the signal pipelines end-to-end: instrument events, build clean labeled datasets, and translate user behaviors into reliable learning signals
• Design lightweight reinforcement learning / bandit-style approaches where appropriate
• Partner closely with product and engineering to define success metrics and optimize for them
• Design and analyze experiments that validate whether learning system changes actually improve real outcomes
• Improve ranking, recommendations and decision making within the agent
• Iterate quickly: Ship → measure → learn → improve

Requirements:

• 5-8 years hands on experience building and shipping ML systems
• Bachelor's or Master's degree in computer science
• Experience shipping ML systems to production and have worked on recommendation systems, ranking, personalization or optimization problems
• Deep knowledge in Python and model ML tooling
• Pragmatic: you choose simple, effective solutions over theoretically perfect ones