AI/ML Engineer: End-to-End ML, MLOps & Data Quality

Apparel Group; United Arab Emirates; On-site; AED 180,000 - 360,000; Full time

Job summary

Apparel Group seeks a senior ML/AI leader to translate business problems into robust machine learning solutions, build end-to-end pipelines, and optimize inference for latency and throughput. You will balance accuracy with fairness and cost considerations across real-time and batch workflows, while collaborating with product teams.

You will own deployment, monitoring, data governance, and scalable ML services using Spark/Databricks, Docker/Kubernetes, and cloud platforms.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or a related field.
• Proven experience designing, training, and deploying ML models and AI solutions.
• Strong programming skills in Python and familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Hands-on experience with MLOps tools and practices (Docker, Kubernetes, MLflow, CI/CD pipelines).
• Proficiency in data processing and ETL tools (Spark, Databricks) and working with large datasets.

Responsibilities

• Model & Solution Engineering Translate business problems into ML formulations; select suitable architectures (e.g., gradient boosting, transformers) with clear success metrics.
• MLOps, Deployment & Observability Implement model versioning, lineage, and experiment tracking; manage rollbacks and canary releases.
• Data Engineering, Quality & Governance Design data contracts; implement ETL/ELT pipelines with testing and backfills; enforce data quality gates.
• Experimentation, Product Integration & Stakeholder Enablement Design experiments, integrate models via APIs/SDKs with business rules; document trade-offs.

Skills

Python programming

ML frameworks

Analytical skills

Communication

Education

Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or a related field

Tools

Docker

Kubernetes

MLflow

Spark

Databricks

Job description

Apparel Group seeks a senior ML/AI leader to translate business problems into robust machine learning solutions, build end-to-end pipelines, and optimize inference for latency and throughput. You will balance accuracy with fairness and cost considerations across real-time and batch workflows, while collaborating with product teams.

You will own deployment, monitoring, data governance, and scalable ML services using Spark/Databricks, Docker/Kubernetes, and cloud platforms.