Product ML Engineer

About the Company

SweedPos is a product-driven startup building an all-in-one cannabis retail platform. Our enterprise-grade platform combines POS, eCommerce, Marketing, Analytics, and Inventory Management into a single, seamless solution, helping retailers drive business growth through innovation and efficiency.

Responsibilities

• Build and improve production recommendation and ranking systems
• Develop personalization models across the eCommerce customer journey
• Work on candidate generation, retrieval, ranking, and re-ranking approaches
• Design personalized product feeds, carousels, and next-best-action experiences
• Contribute to customer behavior, demand, and product-level forecasting
• Connect recommendation systems with search and conversational shopping experiences
• Define and track offline ML metrics and online product metrics
• Design and run experiments and A/B tests to validate product hypotheses
• Build scalable inference services and ML APIs
• Improve feature pipelines, training workflows, monitoring, and internal ML tooling
• Participate in architectural discussions and technical decision-making

Requirements

• 5+ years of production Machine Learning Engineering experience
• Strong commercial experience with recommendation systems
• Proficiency in Python and SQL
• Experience with ranking, retrieval, collaborative filtering, or embeddings
• Experience building and maintaining production ML systems
• Experience with A/B testing and experimentation
• Strong understanding of the full ML lifecycle (experimentation, deployment, monitoring)
• Experience building APIs or production inference services
• Familiarity with MLOps, CI/CD, and observability
• Strong software engineering fundamentals

Preferred Qualifications

• Experience with forecasting or time-series models
• Experience with eCommerce, marketplaces, or advertising products
• Experience with search or information retrieval
• Experience building feature pipelines or feature stores
• Experience building ML systems from an early stage