Machine Learning Engineer - Relevance & Learning Systems

<h2><strong>About Wizard</strong></h2> <p>Wizard is the top-performing AI Shopping Agent, delivering the best products from across the web with unmatched accuracy, quality, and trust.</p> <h2><strong>The Role</strong></h2> <p>We’re looking for a Machine Learning Engineer to design and build feedback driven learning systems that improve our AI agent over time. This is not a traditional RL research role, we’re focused on building systems that learn from real user behavior and improve production. You’ll be working at the intersection of a live conversational agent and real shopping behavior – the feedback signal quality here is unusually rich compared to traditional search.</p> <p>You’ll focus on turning user interactions into learning signals, designing practical feedback loops and shipping systems that continuously improve real world outcomes.</p> <h2><strong>What You’ll Do</strong></h2> <ul> <li>Build and productionize feedback loops that improve agent performance over time</li> <li>Build the evaluation infrastructure – offline metrics, regression suites, and experiment analysis</li> <li>Own the signal pipelines end-to-end: instrument events, build clean labeled datasets, and translate user behaviors into reliable learning signals</li> <li>Design lightweight reinforcement learning / bandit-style approaches where appropriate</li> <li>Partner closely with product and engineering to define success metrics and optimize for them</li> <li>Design and analyze experiments that validate whether learning system changes actually improve real outcomes</li> <li>Improve ranking, recommendations and decision making within the agent</li> <li>Iterate quickly: Ship → measure → learn → improve&nbsp;</li> </ul> <p><strong>What Success Looks like</strong></p> <ul> <li>You ship quickly and drive measurable improvements in core product metrics</li> <li>You turn noisy user behavior into reliable learning signals that improve the agent over time</li> <li>You own systems end to end and operate comfortably in production</li> </ul> <h2><strong>Ideal Background</strong></h2> <ul> <li>5-8 years hands on experience building and shipping ML systems</li> <li>Bachelor’s or Master's degree in computer science</li> <li>Experience shipping ML systems to production and have worked on recommendation systems, ranking, personalization or optimization problems</li> <li>Deep knowledge in Python and model ML tooling</li> <li>Pragmatic: you choose simple, effective solutions over theoretically perfect ones</li> </ul> <h3><strong>Compensation &amp; Benefits</strong></h3> <p>The expected base salary range for this role is $225,000 - $280,000 USD, and will vary based on skills, experience, role level, and geographic location. Final compensation will be determined by considering these factors alongside overall role scope and responsibilities.</p> <p>In addition to base salary, Wizard offers:</p> <ul> <li>Equity in the form of stock options</li> <li>Medical, dental, and vision coverage</li> <li>401(k) plan</li> <li>Flexible PTO and company holidays</li> <li>Fully remote work within the United States</li> <li>Periodic company offsites and team gatherings</li> </ul> <p>Wizard is committed to fair, transparent, and competitive compensation practices.</p>