About the Job:
As the leading delivery company in the region, talabat has a significant responsibility and opportunity to positively impact the lives of millions of customers, restaurant partners, and riders. We aim to scale and enhance our machine learning capabilities across the company, necessitating robust, efficient, and scalable ML platforms that enable teams to build, deploy, and operate intelligent systems quickly and reliably.
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As an ML Platform Engineer, your mission will be to build and maintain the infrastructure and tooling that accelerates the development, deployment, and monitoring of machine learning models in production. You'll collaborate closely with data scientists, ML engineers, and product teams to design seamless ML workflows—from experimentation to serving—while ensuring high operational excellence in our ML systems.
Key Responsibilities:
- Design, build, and maintain scalable, reusable, and reliable machine learning platforms and tooling to support the full ML lifecycle: data ingestion, training, evaluation, deployment, and monitoring.
- Collaborate with ML practitioners to understand their workflows and abstract them into flexible platform components and services.
- Automate and streamline ML model training pipelines, model versioning, artifact management, and deployment workflows using modern MLOps practices.
- Integrate infrastructure components (e.g., feature stores, model registries, experiment tracking, orchestration engines) and cloud-native services to build robust systems.
- Ensure reliability, observability, and scalability of production ML workloads; implement monitoring, alerting, and performance evaluation for deployed models.
- Drive engineering best practices within the ML platform including CI/CD, testing, documentation, and performance optimization.
- Partner with data engineering, product, and infrastructure teams to align ML platform initiatives with broader company goals and architecture.
Requirements:
- Bachelor's degree in Computer Science, Engineering, or a related field (a postgraduate degree is a plus but not required).
- 3+ years of experience in ML platform, ML infrastructure, or related roles.
- Strong software engineering background with experience in building distributed systems or platforms, ideally focused on ML/AI use cases.
- Proficiency in Python and experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
- Hands-on experience with ML infrastructure tooling, orchestration frameworks (e.g., Airflow, Flyte), and containerization (Docker, Kubernetes).
- Familiarity with CI/CD pipelines, version control, and infrastructure-as-code (e.g., Terraform).
- Experience working with cloud platforms, preferably Google Cloud Platform (GCP).
- Strong understanding of model lifecycle management and familiarity with SQL is required.
Language Requirements:
- Proficiency in English is expected.
Company Overview:
Since launching in Kuwait in 2004, talabat has established itself as the leading on-demand food and Q-commerce app for everyday deliveries. With local roots in eight countries across the region, talabat is dedicated to simplifying everyday life for customers, optimizing operations for restaurants and local shops, and providing riders with reliable earning opportunities. We are committed to building a high-performance culture through engaged workforce and growing talent density, aiming to spread positive vibes throughout our mission.
