Machine Learning Engineer: Personalization

As part of the Personalization team, you will help shape the e-commerce experience for hundreds of millions of shoppers worldwide. You will design, deliver, and maintain high-load, real-time machine learning services that power personalized experiences across products, platforms, and domains. Your work will focus on understanding user interactions and turning behavioral signals into relevant, impactful recommendations and experiences. You will research and test personalization approaches, using experimentation and data to validate hypotheses and improve key business metrics. You will work closely with machine learning and engineering teams, including teams responsible for ranking and search, to build cohesive experiences. The role combines hands-on applied machine learning with product thinking, stakeholder collaboration, and end-to-end ownership. You will join an open, cooperative, fully remote environment where autonomy, empathy, and measurable impact are highly valued. Accountabilities

• Develop and improve personalized experiences across different products, platforms, and e-commerce domains.
• Design, build, ship, and maintain high-load, real-time machine learning services supporting personalization at scale.
• Model user interactions and behavioral signals to better understand shopper preferences and deliver relevant experiences.
• Research and evaluate different personalization and recommendation approaches to identify opportunities for improvement.
• Formulate and validate hypotheses around personalization using data, experimentation, and A/B testing.
• Analyze the impact of personalization initiatives and identify opportunities to improve key business performance indicators.
• Collaborate closely with technical and non-technical stakeholders to develop, refine, and evolve personalization capabilities.
• Work cross-functionally with engineering and machine learning teams, including ranking teams, to deliver integrated solutions.
• Communicate technical findings, recommendations, and business value clearly to stakeholders within and beyond the team.
• Take ownership of problems from investigation and experimentation through implementation and continuous improvement.

• 3+ years of professional experience in applied machine learning.
• Strong proficiency in Python and SQL, with experience using the big data stack for end-to-end machine learning product development.
• Proven experience building, deploying, and maintaining personalization, recommendation, or ranking systems in production.
• Practical understanding of machine learning development in high-scale, production environments.
• Experience designing and analyzing A/B tests and using experimental results to guide product or model decisions.
• Experience translating machine learning initiatives into measurable business value and communicating that value effectively to stakeholders.
• Experience with one or more major public cloud platforms is a plus.
• Excellent English communication skills, both written and verbal.
• Experience working effectively in cross-functional teams with technical and non-technical colleagues.
• Strong analytical and problem-solving skills, with the ability to investigate complex problems and turn findings into actionable outcomes.
• Ability to work autonomously, take ownership, and make progress independently.
• Proactive mindset with a strong focus on collaboration, learning, and delivering meaningful impact.

• Fully remote working environment, giving you flexibility over where you live.
• Unlimited vacation time, with employees strongly encouraged to take at least 3 weeks of vacation each year.
• Work-from-home stipend to help you create a well-equipped home office.
• Apple laptop provided for new employees.
• Annual training and professional development budget.
• Maternity and paternity leave for eligible employees.
• Regular team offsite events to connect and collaborate.
• Opportunity to work with talented and empathetic colleagues who support your growth and enable you to make a meaningful impact.
• Base salary of $80,000-$120,000 USD, depending on knowledge, skills, experience, and interview results.
• Stock options offered in addition to the base salary.