Since launching in Kuwait in 2004, talabat has grown to become the leading on-demand food and Q-commerce app for everyday deliveries, serving communities across eight countries in the region. We prioritize innovation, harnessing technology to simplify life for customers, optimize operations for restaurants and local shops, and provide our riders with reliable earning opportunities. Our mission extends to creating a high-performance culture through an engaged workforce and growing talent density.
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As the leading delivery platform in the region, we face the unique responsibility of positively impacting millions of customers, restaurant partners, and riders. To achieve this mission, we are scaling and evolving our machine learning capabilities, particularly in Generative AI (genAI) initiatives. This role requires constructing robust, efficient, and scalable ML platforms that enable our teams to quickly develop, deploy, and manage intelligent systems.
Responsibilities:
- Design, build, and maintain scalable ML platforms supporting the entire ML lifecycle.
- Develop standardized ML workflows and templates for rapid experimentation and deployment.
- Implement CI/CD pipelines, Docker containerization, model registries, and experiment tracking.
- Collaborate with genAI experts to optimize technologies and streamline workflows.
- Ensure reliability and observability of production ML workloads by implementing monitoring and evaluation.
- Integrate infrastructure components for robust production environments.
- Optimize infrastructure for generative AI use cases and model updates at scale.
- Work with cross-functional teams to align ML initiatives with broader company goals.
- Contribute to internal documentation and training programs for platform adoption.
Requirements:
- Strong software engineering background with experience in distributed systems for ML and AI workloads.
- Expert-level proficiency in Python and familiarity with ML frameworks (e.g., TensorFlow, PyTorch).
- Experience with MLOps practices including CI/CD, Docker, Kubernetes, and infrastructure-as-code tools.
- Proven ability to work with cloud infrastructure (AWS or GCP) and implement ML services.
- Familiarity with generative AI technologies and experience with real-time inference pipelines.
- Analytical skills with SQL and data management capabilities.
Qualifications:
- Bachelor’s degree in Computer Science, Engineering, or related field; advanced degree preferred.
- 2+ years in a tech lead role and 5+ years in ML platform engineering or related fields.
- Proven success in building and operating ML infrastructure at scale, particularly for generative AI.
- Strong problem-solving skills with effective decision-making abilities.
- Excellent communication and collaboration skills across diverse teams and stakeholders.
- Sense of ownership and proactive bias for action.
