Machine Learning Engineer - Relevance & Learning Systems

About WizardWizard is the top-performing AI Shopping Agent, delivering the best products from across the web with unmatched accuracy, quality, and trust.The RoleWe’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.You’ll focus on turning user interactions into learning signals, designing practical feedback loops and shipping systems that continuously improve real world outcomes.What You’ll DoBuild and productionize feedback loops that improve agent performance over timeBuild the evaluation infrastructure – offline metrics, regression suites, and experiment analysisOwn the signal pipelines end-to-end: instrument events, build clean labeled datasets, and translate user behaviors into reliable learning signalsDesign lightweight reinforcement learning / bandit-style approaches where appropriatePartner closely with product and engineering to define success metrics and optimize for themDesign and analyze experiments that validate whether learning system changes actually improve real outcomesImprove ranking, recommendations and decision making within the agentIterate quickly: Ship → measure → learn → improve What Success Looks likeYou ship quickly and drive measurable improvements in core product metricsYou turn noisy user behavior into reliable learning signals that improve the agent over timeYou own systems end to end and operate comfortably in productionIdeal Background5-8 years hands on experience building and shipping ML systemsBachelor’s or Master's degree in computer scienceExperience shipping ML systems to production and have worked on recommendation systems, ranking, personalization or optimization problemsDeep knowledge in Python and model ML toolingPragmatic: you choose simple, effective solutions over theoretically perfect onesCompensation & BenefitsThe 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.In addition to base salary, Wizard offers:Equity in the form of stock optionsMedical, dental, and vision coverage401(k) planFlexible PTO and company holidaysFully remote work within the United StatesPeriodic company offsites and team gatheringsWizard is committed to fair, transparent, and competitive compensation practices.Originally posted on Himalayas