We are hiring on behalf of our client, a global leader in the meal kit delivery industry that helps millions of customers enjoy healthy, home-cooked meals with less planning and effort.

As part of Zoolatech, you will join a team building intelligent, ML-driven experiences across the client’s digital platforms. The team is transforming traditionally static experiences into dynamic systems that power recipe recommendations, content tagging, collections, ranking, and SEO-related features.

In this role, you’ll work on production-grade ML and LLM-powered solutions that directly influence customer experience and business impact. You’ll collaborate with international teams in a fast-moving environment that values ownership, proactive communication, and the ability to turn ideas into real-world AI solutions.

• Design and improve ML and LLM-powered solutions for content personalization and customer experiences

• Build scalable data pipelines for processing and transforming large-scale text data

• Develop retrieval, ranking, and recommendation systems to improve content quality and relevance

• Design evaluation frameworks for LLM outputs, including quality, safety, and performance metrics

• Monitor model performance and business impact through experiments, dashboards, and data analysis

• Collaborate with cross-functional teams to translate business needs into production-ready ML solutions

• Take ownership of features and initiatives from idea to launch

• Strong experience with LLM evaluation frameworks, including human review, automated checks, and quality evaluation (safety, tone, factuality)

• Solid understanding of retrieval and ranking metrics (Hit@K, Recall@K, Precision@K) and performance measurement principles

• Strong SQL skills and experience building dashboards and analytical views in Databricks or lakehouse environments

• Strong Python skills for scalable data pipelines and large-scale text processing

• Experience with embeddings and semantic similarity techniques, including clustering and duplicate detection

• Strong experimentation mindset with experience in monitoring, measurement, and model performance evaluation

• Ability to translate ML decisions into business impact and product outcomes

• Strong ownership, adaptability, and ability to work effectively in ambiguous environments

• Strong communication skills and proactive approach

• Experience with SEO and product analytics concepts

• Experience with multilingual NLP

• Knowledge of graph algorithms and clustering techniques

• Experience with reranking approaches and semantic search optimization

• LLM calibration and evaluation tuning experience

• Hands-on experience with MLOps and production ML environments (Databricks, MLflow, batch inference, etc.)

• Experience with content safety and governance workflows

• Experience designing human-in-the-loop review and approval processes

Benefits:

• Paid Vacation
• Sick Days
• Floating Holidays
• Sport/Insurance Compensation
• English Classes
• Charity
• Training Compensation