Zipify builds high-impact Shopify apps that help merchants maximize revenue and conversion. Our flagship product, OneClickUpsell (OCU), has generated over $1.2B in upsell revenue for merchants. We are evolving beyond traditional SaaS into a hybrid model that combines product, AI, and high-value services to deliver measurable growth for ecommerce brands.
We’re looking for an AI/ML Engineer to join our product team to operate across Zipify’s product ecosystem, including OCU, Zipify Pages, and emerging AI-driven products. This is not a classic ML role — we’re looking for someone with a strong AI engineering mindset: building intelligent systems, working with LLMs, and turning models into real product features.
This is a hands-on role at the intersection of AI/ML, product, and data. The ideal candidate is comfortable building AI-powered functionality, working with structured data, and contributing to data-related engineering tasks when needed. What We Value in a New Master * 3+ years Python hands-on experience with pandas and NumPy. * Strong SQL skills and comfort working with databases in day-to-day tasks. * Solid understanding of ML fundamentals: classification, clustering, regression — and hands-on experience building such models. * Experience working with LLM APIs and prompt engineering. * Understanding of how to design and build practical agentic systems. * Comfort working with real-world product data and data pipelines. * Git, Docker — comfortable day-to-day usage. * English level: Upper-Intermediate or higher.
Nice to Have * AWS stack: SageMaker, S3, Lambda, and related services. * Data engineering experience: Airflow, dbt. * Experience with recommender systems, experimentation, or A/B testing. * Experience with Streamlit. * Background in e-commerce, SaaS, marketplace, or other product-driven environments. * Portfolio with relevant projects.
How You’ll Contribute * Design and build AI-powered features, including LLM-based and agentic systems. * Integrate and work with LLM APIs (OpenAI, Claude, etc.). * Identify patterns and dependencies in structured and behavioral data to generate actionable insights. * Build recommendation and decisioning systems that improve user interaction with the product. * Design workflows that combine LLMs, structured data, and business logic. * Collaborate with data and product teams to bring experiments into production. * Contribute across the full cycle — from prototype to deployed solution, evaluation, monitoring, and iteration.
