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CORE RESPONSIBILITIES:

End-to-End Engineering: Design, develop, and deploy robust ML systems and multi-model AI agents that solve real-world retail challenges.
MLOps Ownership: Lead the entire lifecycle, including prototyping, deployment, monitoring, and maintenance using modern CI/CD and containerisation practices.
Architectural Leadership: Build high-performance data pipelines ETLELT for both training and real-time inference.

PRODUCT-MINDED ENGINEERING:

User-Centric Focus: Build models to solve specific problems for our customers and internal teams.
Outcome over Output: Prioritise delivering a working solution that solves a business challenge
Iterative Discovery: Work in the "grey area," using data and user feedback to refine your technical approach.

YOUR SKILLS & EXPERTISE:

ML Fundamentals: Strong proficiency in Python and frameworks like PyTorch, TensorFlow, or Scikit-learn
Agentic AI: Hands-on experience with modern AI orchestration tools such as LangChain and LangSmith.
Production Excellence: Proven experience with Docker, Kubernetes, and cloud infrastructure AWS/GCP/Azure

EDITED

EDITED is the world’s leading AI-driven retail intelligence platform. They empower the world’s most successful brands and retailers with real-time decision making power. Their environment is dynamic and supportive, encouraging team members to take initiative, innovate, and continuously grow.

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