ML Platform Engineer

Glow Beauty On Demand

Job Title
ML Platform Engineer Generative AI & Machine Learning Infrastructure
Job Description
ML Platform Engineer Generative AI & Machine Learning Infrastructure

Location: Dubai, UAE
Industry: Technology / AI / Food & Q-commerce
Function: Machine Learning Engineering
Gender: Any
Candidate Nationality: Any
Job Type: Full-time

Role Overview
Talabat, the leading on-demand food and Q-commerce app in the region, is seeking an experienced ML Platform Engineer to design, develop, and scale robust machine learning and generative AI platforms. The role involves building end-to-end ML infrastructure, enabling fast experimentation, efficient model deployment, and seamless monitoring to support next-generation AI-driven solutions for millions of users.

Key Responsibilities

* Build scalable ML platforms supporting data ingestion, model training, deployment, and monitoring for both traditional ML and generative AI models
* Design standardized ML workflows using tools like MLflow, Kubeflow, and implement CI/CD pipelines with Docker and Kubernetes
* Optimize generative AI deployments involving transformers, embeddings, RAG systems, and vector databases such as Pinecone, Redis, or Weaviate
* Implement real-time serving frameworks like TensorFlow Serving, NVIDIA Triton, or Seldon for production-grade inference
* Automate model lifecycle management and implement observability measures to track performance, detect drift, and maintain reliability
* Collaborate with data engineering and product teams to align ML infrastructure with strategic business goals
* Drive cloud infrastructure integration using AWS or GCP services, including Kubernetes clusters, managed ML services, and serverless components
* Ensure cost efficiency, performance optimization, and adherence to best practices for MLOps and generative AI workflows

Qualifications and Experience

* Bachelor s degree in Computer Science, Engineering, or related field (Master s preferred)
* Minimum 3 years of experience in ML platform engineering, MLOps, or generative AI infrastructure roles
* Expertise in Python, ML frameworks (TensorFlow, PyTorch), and APIs such as Hugging Face and LangChain
* Hands-on experience with containerization, orchestration (Docker, Kubernetes), and infrastructure-as-code tools (Terraform, Helm)
* Proven ability to build real-time inference pipelines integrated with feature stores and streaming platforms like Kafka or Kinesis
* Familiarity with SQL for data processing and knowledge of observability tools for monitoring AI systems
* Strong understanding of model optimization techniques including quantization, batching, and prompt-tuning strategies