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 to its customers across eight countries in the region. Talabat is committed to building a high-performance culture by engaging its workforce and enhancing talent density. The company aims to make a positive impact on millions of customers, restaurant partners, and riders through innovative technology and knowledge.
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As an ML Platform Engineer, your mission will be to design, build, and enhance the infrastructure and tooling that accelerates the development, deployment, and monitoring of traditional machine learning (ML) and generative AI (genAI) models at scale. You will work collaboratively with data scientists, ML engineers, genAI specialists, and product teams to ensure seamless ML workflows—covering everything from experimentation to production serving—and to maintain operational excellence in the ML and genAI systems.
Responsibilities:
- Design, build, and maintain scalable ML platforms and tools that support the entire ML lifecycle, covering data ingestion, training, evaluation, deployment, and monitoring for both traditional and generative AI models.
- Develop standardized ML workflows using MLflow and other platforms for rapid experimentation and deployment.
- Implement CI/CD pipelines, Docker containerization, and model registries to enhance reproducibility and scalability.
- Collaborate with genAI experts to integrate and optimize genAI technologies.
- Automate and streamline ML and genAI model workflows, ensuring reliability and adherence to industry best practices.
- Ensure observability and scalability of production ML and genAI workloads.
- Integrate infrastructure components for robust production environments.
- Partner with cross-functional teams to align ML platform initiatives with company goals.
Requirements:
- Strong software engineering background with experience in distributed systems for ML and AI workloads.
- Expertise in Python and familiarity with ML frameworks (e.g., TensorFlow, PyTorch).
- Experience with MLOps practices, CI/CD, Docker, Kubernetes, and infrastructure-as-code tools.
- Comfort with cloud infrastructure (e.g., AWS, GCP) and managed ML services.
- 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 preferred.
- 3+ years of experience in ML platform engineering or closely related roles.
- Track record of successfully building ML infrastructure at scale.
- Strong problem-solving skills and effective technical decision-making abilities.
- Excellent communication and collaboration skills, with a proactive approach.
Join talabat and contribute to our mission to simplify everyday life for our customers and make a positive impact in the communities we serve.
