Middle ML Engineer (e-commerce) (вакансія неактивна)

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.
• 1+ years of ML experience: classification, clustering, regression — and hands-on experience building such models.
• Strong SQL skills and comfort working with databases in day-to-day tasks.
• 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.