Machine Learning Engineer: Recommendations (Remote), Remote Job

Remote Full-time
About The Team

Launched in 2019, Constructor is an AI-first ecommerce search and discovery platform that helps shoppers find the right products at the right time and enables leading global e-commerce brands to drive meaningful revenue and conversion gains.

As a member of the Recommendations team, you will apply cutting-edge Machine Learning techniques to build the best recommendations-as-a-service product on the market, transforming the ecommerce experience for hundreds of millions of users worldwide.
You will:
• Build high-load, real-time recommendation service.
• Build end-to-end ML pipelines driving measurable business impact.
• Design metrics to evaluate recommendation relevance and performance.
• Lead the full development lifecycle from initial design to production.
• Participate in strategic planning to help drive product evolution and prioritization.
• Collaborate with stakeholders to align technical roadmaps with business needs.

Requirements
• Deep understanding of ML fundamentals and experience building large-scale recommendation, retrieval, or ranking systems.
• Expertise in Python and SQL, with hands-on experience in big data systems (e.g., Spark, Presto/Athena, Hive).
• Production-level ML experience, including deploying models to production and designing A/B tests to validate business impact.
• Analytical mindset with the ability to translate intuition into data-driven hypotheses and high-value engineering solutions.
• Excellent communication skills in English, capable of explaining complex technical concepts to non-technical stakeholders.

Benefits

️ Unlimited vacation time - we strongly encourage all employees to take at least 3 weeks per year

Fully remote team - choose where you live

️ Work from home stipend - we want you to have the resources you need to set up your home office

Apple laptops provided for new employees

‍ Training and development budget - refreshed each year for every employee

Maternity & Paternity leave for qualified employees

Work with smart people who will help you grow and make a meaningful impact

Base salary: $80k–$120k USD, depending on knowledge, skills, experience, and interview results

Stock options - offered in addition to the base salary

Regular team offsites to connect and collaborate

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