Senior Data Science Engineer

Zoolatech
Hong Kong, HK
On-site

Why this role

Pace
Fast Paced
Collaboration
High
Autonomy
Medium
Decision Impact
Team
Role Level
Team Lead

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • 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
Typical background
Data ScienceMachine Learning

Transferable backgrounds

  • Coming from Data Science
  • Coming from Machine Learning

Skills & requirements

Required

PythonLLM Evaluation FrameworksSQLData VisualizationStrong Analytical Skills

Preferred

Experience With SEO And Product Analytics ConceptsKnowledge Of Graph Algorithms And Clustering Techniques

Stack & domain

Llm Evaluation FrameworksRetrieval And Ranking MetricsSQLPythonEmbeddingsSemantic Similarity TechniquesMlopsProduction Ml EnvironmentsContent Safety And Governance WorkflowsHuman-in-the-loop Review And Approval ProcessesOwnershipAdaptabilityCommunicationProactive ApproachData ScienceMachine Learning

About the role

Original posting from Zoolatech via Indeed

OVERVIEW

RESPONSIBILITIES

REQUIREMENTS

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

Location:

Other, Central Europe

Seniority:

Senior

Technologies:

Data Science, Machine Learning

Benefits:

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

Source: Zoolatech careers (Indeed)

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