Engineering Manager, Applied AI & LLM Automation

Delivery Hero SE; Abu Dhabi; On-site; AED 700,000 - 900,000; Full time

Job summary

talabat is seeking a Manager, Data Scientist - AI to lead a team of data scientists within the Applied AI Tribe. You will own the roadmap and delivery of ML and generative AI systems powering product and business decisions at scale.

You will work closely with product, engineering, and leadership to frame problems, design experiments, and deliver measurable impact through data enrichment and automated decision-making.

Qualifications

• 6+ years in data science, ML engineering, and/or generative AI, including shipping models to production.
• 2+ years managing or leading a data science or ML team, with a track record of developing talent.
• Experience building ML systems in an online consumer product environment is a strong plus.
• Strong Python, SQL, and statistics foundations; experience with A/B testing and causal inference.

Responsibilities

• Lead a team of data scientists, setting high technical quality and ownership standards.
• Own the team's technical roadmap: ML/AI, data enrichment, automation, and agentic features.
• Oversee full ML lifecycle from data pipelines to deployment and monitoring.
• Drive adoption of LLMs and generative AI for automated decisions and intelligent experiences at scale.
• Collaborate with product managers, biz teams, and engineering to align on value and delivery.
• Elevate ML engineering standards, MLOps, tooling, and evaluation pipelines.

Skills

ML & GenAI

NLP

Data modelling

Experiment design

Python

SQL

Education

Bachelor's in Engineering/CS

Postgraduate degree a plus

Tools

Scikit-learn

XGBoost

LightGBM

PyTorch

TensorFlow

Transformers

OpenAI SDK

LangGraph

Hugging Face

BigQuery/GCP

Job description

talabat is seeking a Manager, Data Scientist - AI to lead a team of data scientists within the Applied AI Tribe. You will own the roadmap and delivery of ML and generative AI systems powering product and business decisions at scale.

You will work closely with product, engineering, and leadership to frame problems, design experiments, and deliver measurable impact through data enrichment and automated decision-making.