Applied AI Manager

About the role

Lead the Applied AI Tribe as Manager, Data Scientist – AI, guiding a team that builds and ships machine learning and generative AI systems across talabat’s product and business. You will own the roadmap, drive technical decisions, and ensure measurable AI value delivery.

Key responsibilities

• Lead, grow, and retain a high‑performing team of data scientists, setting technical standards and supporting career development.
• Translate ambiguous business problems into scoped ML solutions with clear success metrics tied to Net AI Value Delivered.
• Own the technical roadmap, prioritising high‑impact work in data enrichment, business automation, self‑serve tooling, and agentic product features.
• Ensure harness‑first thinking, evaluation pipelines, LLM observability, and production feedback loops are in place.
• Oversee the full ML lifecycle: data pipelines, feature engineering, model training, deployment, serving, and monitoring.
• Partner with product managers, engineering, and business teams to identify AI opportunities and communicate results to senior stakeholders.

Required profile

• 6+ years of experience in data science, ML engineering, or generative AI, with a track record of shipping models to production.
• 2+ years of experience managing or leading a data science/ML team.
• Bachelor’s degree in Engineering, Computer Science or related field; postgraduate degree a plus.
• Experience building ML systems for online consumer products is a strong plus.

Required skills

• Machine learning, deep learning, NLP, recommendation systems, data mining.
• Frameworks: Scikit‑learn, XGBoost, LightGBM, PyTorch, TensorFlow, Transformers, LLM fine‑tuning.
• OpenAI SDK, major LLM provider APIs, LangGraph, Hugging Face (Transformers, Hub, Inference API).
• Embeddings, vector databases, semantic search, RAG pipelines.
• Python, SQL, Airflow, MLOps practices, production code quality.
• BigQuery and Google Cloud Platform (optional).