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Since launching in Kuwait in 2004, talabat has become the leading on-demand food and Q-commerce app for everyday deliveries, providing convenience and reliability to its customers across eight countries in the region. Talabat harnesses innovative technology to simplify daily life for customers, optimize operations for restaurants and local shops, and offer reliable earning opportunities for riders.
As the leading delivery platform, talabat has a unique responsibility to positively impact millions of customers, restaurant partners, and riders. The company aims to scale and continuously evolve its machine learning capabilities, particularly in Generative AI (genAI) initiatives.
As a Sr. MLOps Engineer, you will design, build, and enhance the infrastructure and tooling that accelerates the development, deployment, and monitoring of both traditional machine learning and genAI models at scale. You will collaborate closely with data scientists, ML engineers, genAI specialists, and product teams to deliver seamless ML workflows from experimentation to production serving, ensuring operational excellence across the ML and genAI systems.
Responsibilities:
- Design, build, and maintain scalable ML platforms and tooling that support the entire ML lifecycle, including data ingestion, model training, evaluation, deployment, and monitoring for both traditional and generative AI models.
- Develop standardized ML workflows and templates enabling rapid experimentation and deployment cycles.
- Implement CI/CD pipelines, Docker containerization, model registries, and experiment tracking to support reproducibility and governance.
- Collaborate with genAI experts to integrate and optimize genAI technologies.
- Automate and streamline model training, inference, deployment, and versioning workflows.
- Ensure reliability and observability of production ML and genAI workloads.
- Integrate infrastructure components for robust production environments.
- Drive optimization for generative AI use cases.
- Partner with various teams to align ML platform initiatives with company goals.
- Contribute to documentation, onboarding, and training programs.
Requirements:
- Strong software engineering background with experience in building systems for machine learning and AI workloads.
- Proficiency in Python and familiarity with ML frameworks (TensorFlow, PyTorch) and infrastructure tooling (MLflow, Kubeflow).
- Experience implementing modern MLOps practices, including CI/CD, Docker, and Kubernetes.
- Experience with cloud infrastructure, ideally AWS or GCP.
- Proven experience with generative AI technologies and real-time inference pipelines.
- Familiarity with SQL and data warehouse modeling.
- Understanding of ML monitoring and scaling API-based genAI applications.
Qualifications:
- Bachelor’s degree in Computer Science, Engineering, or a related field; advanced degree is a plus.
- 3+ years of experience in ML platform engineering or related roles.
- Proven track record of building and operating ML infrastructure at scale.
- Strong problem-solving skills and effective technical decision-making abilities.
- Excellent communication and collaboration skills.
- Strong sense of ownership and proactive approach.
Location:
Dubai, Dubai, United Arab Emirates
Work Conditions:
On-site, Full-time
Language Requirements:
Not specified.
