AI ML Engineer

Job Title: AI ML Engineer Company: Apparel Group Job Category: Machine Learning Roles & Responsibilities: Key responsibilities * Model \& Solution Engineering  Translate business problems into ML formulations; select suitable architectures (e.g., gradient boosting, transformers) with clear success metrics.  Build end\-to\-end pipelines: feature extraction, training, hyperparameter tuning, and packaging models as reproducible artifacts.  Optimize inference (quantization, distillation, mixed precision) for latency and throughput on CPU/GPU.  Conduct evaluation beyond accuracy (calibration, fairness, cost\-sensitive metrics, PR/ROC under imbalance). * MLOps, Deployment \& Observability  Implement model versioning, lineage, and experiment tracking; manage rollbacks and canary releases.  Build real\-time and batch inference services; integrate with message buses and vector databases.  Monitor for schema checks, data drift, performance regression, and cost observability.  Create alerting and autoscaling policies tied to SLAs, maintain incident runbooks for model services * Data Engineering, Quality \& Governance  Design data contracts; implement ETL/ELT pipelines (e.g., Spark/Databricks) with testing and backfills.  Enforce data quality gates and schema evolution strategies to prevent mismatches.  Apply privacy\-by\-design: PII handling, tokenization, and secure secrets management.  Collaborate on cost\-efficient data architectures (tiering, caching, Parquet/Delta formats) * Experimentation, Product Integration \& Stakeholder Enablement  Design experiments (A/B, counterfactual evaluation); define guardrails and success criteria with product teams.  Integrate models via APIs/SDKs with business rules and fallbacks for graceful degradation.  Produce clear documentation (model cards, decision logs) and present trade\-offs to stakeholders. Work Location: United Arab Emirates Availability: Full time

Qualifications \& Skills  Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or a related field.  Proven experience in designing, training, and deploying machine learning models and AI solutions.  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.  Understanding of data governance, privacy standards, and compliance requirements. Key Skills: Machine Learning, Python, TensorFlow, PyTorch Salary: Not disclosed