Machine Learning Engineer - Relevance & Learning Systems

Posted 21 Days Ago
Easy Apply
Hiring Remotely in USA
Remote
225K-280K Annually
Senior level
Artificial Intelligence • eCommerce • Software
The Role
The Machine Learning Engineer will design and build systems that improve the AI shopping agent by using real user feedback, focusing on feedback loops and metrics to enhance user interactions and agent performance.
Summary Generated by Built In
About Wizard

Wizard is the top-performing AI Shopping Agent, delivering the best products from across the web with unmatched accuracy, quality, and trust.

The Role

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.

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 Do
  • 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 

What Success Looks like

  • You ship quickly and drive measurable improvements in core product metrics
  • You turn noisy user behavior into reliable learning signals that improve the agent over time
  • You own systems end to end and operate comfortably in production
Ideal Background
  • 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
Compensation & Benefits

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.

In addition to base salary, Wizard offers:

  • Equity in the form of stock options
  • Medical, dental, and vision coverage
  • 401(k) plan
  • Flexible PTO and company holidays
  • Fully remote work within the United States
  • Periodic company offsites and team gatherings

Wizard is committed to fair, transparent, and competitive compensation practices.

Top Skills

Machine Learning Tooling
Python
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The Company
HQ: New York City, New York
77 Employees
Year Founded: 2021

What We Do

Wizard AI is powering the future of commerce through conversation. Our full-service B2B solution empowers brands to sell, market, and engage their customers directly via text, resulting in conversion rates 10x higher than ecommerce. Cofounded by Marc Lore, Wizard is backed by a $50M Series A round led by NEA and Accel, and is on a mission to build the dominant technology in the space. We're hiring the best talent and we'd love for you to join us! We’re proud of our commitment to diversity and inclusivity—and we invest in your career by creating a workplace that values transparency and flexibility, and offers remote/hybrid work options. To learn more about Wizard, review our open roles, or request a demo, visit www.wizard.com. We'd love to hear from you!

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