Since launching in Kuwait in 2004, talabat has become the leading on-demand food and Q-commerce app for everyday deliveries, offering convenience and reliability across eight countries in the region. At talabat, we aim to simplify everyday life for our customers, optimize operations for restaurants and local shops, and provide reliable earning opportunities for our riders.
Ready to apply for roles like this?
Unlock the company name and direct application link. Subscribers get instant access to fresh jobs across Dubai, Abu Dhabi and Riyadh, many with visa support.
Unlock employer & apply directly
As the leading delivery platform in the region, we have a unique responsibility to positively impact millions of customers, restaurant partners, and riders. To achieve our mission, we are scaling our machine learning capabilities, including initiatives in Generative AI (genAI). This requires robust, efficient, and scalable ML platforms that empower our teams to rapidly develop and operate intelligent systems.
As an ML Platform Engineer, you will design, build, and enhance the infrastructure and tooling that accelerates the development, deployment, and monitoring of traditional ML and genAI models at scale. You will collaborate with data scientists, ML engineers, genAI specialists, and product teams to deliver seamless ML workflows, ensuring operational excellence across our ML and genAI systems.
Key Responsibilities:
- Design, build, and maintain scalable ML platforms and tooling that support the entire ML lifecycle.
- Develop standardized ML workflows and templates using MLflow and other platforms.
- Implement robust CI/CD pipelines, Docker containerization, and experiment tracking.
- Collaborate with genAI experts to integrate and optimize genAI technologies.
- Automate and streamline ML and genAI model training, inference, and deployment workflows.
- Ensure reliability and observability of production ML workloads through monitoring and performance evaluation.
- Integrate infrastructure components for robust production environments.
- Drive infrastructure optimization for generative AI use-cases.
- Partner with cross-functional teams to align ML platform initiatives with company goals.
Requirements:
- Strong software engineering background with experience in distributed systems or platforms for machine learning.
- Expert-level proficiency in Python and familiarity with ML frameworks (TensorFlow, PyTorch).
- Experience in implementing MLOps practices, including CI/CD and infrastructure-as-code tools.
- Demonstrated 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.
Qualifications:
- Bachelor’s degree in Computer Science, Engineering, or related field; advanced degree is a plus.
- 3+ years of experience in ML platform engineering or related roles.
- Strong problem-solving skills and effective technical decision-making abilities.
- Excellent communication and collaboration skills across diverse teams.
- Strong sense of ownership and proactive bias for action.
