Wizard
Machine Learning Engineer- Relevance & Learning Systems
Rol remoto de Machine Learning Engineer con fit claro de ubicación del candidato.
Publicado1 jul 2026
Países elegibles1 país aceptado
Señal de senioritySenior
Modelo de trabajoRemoto
Ubicaciones aceptadas para candidatos
Estados Unidos
Resumen del rol
Machine Learning Engineer- Relevance & Learning Systems
Requisitos y responsabilidades
Contenido del rol extraído en secciones para revisar más rápido.
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
- 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
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