AI Engineer

WE TAKE YOU ABOVE BEYOND

Take your passion to the next level and work alongside other masters of their craft to build a fulfilling and rewarding career at Marina Bay Sands.

Job Summary

You will participate in end-to-end computer vision solutioning—from data strategy and model selection to validation, deployment, and monitoring. Beyond CV, you’ll contribute broader AI/ML capabilities where valuable. Your focus: build reliable models that generalize in production, with strong data practices and measurable outcomes.

Job Responsibilities

• Own CV model lifecycle: Problem framing, dataset design/labeling strategy, model selection, training, hyperparameter tuning, evaluation, and deployment.
• Data sanitization & engineering: Create pipelines for data quality (de-duplication, balance, augmentation), privacy/compliance, and annotation workflows; design versioned datasets.
• Model validation & monitoring: Define metrics (mAP/F1/ROC-AUC/latency), implement drift/shift detection, set acceptance gates, and maintain post-deploy monitoring loops.
• MLOps excellence: Build reproducible training, experiment tracking, artifact management, and automated model promotion (staging → prod) with rollback.
• Cross-functional delivery: Partner with software engineers to translate ambiguous goals into deployable CV solutions that fit live workflows.
• Knowledge sharing & governance: Author technical docs; set standards for labeling, bias checks, and reproducibility.
  
  

Job Requirements

Education & Certification

• Bachelor’s degree in Electrical Engineering, Mechanical Engineering, Computer Science, or related field preferred
  
  

Experience

• 4–8 years in AI/ML with a strong emphasis on computer vision (classification, detection, tracking, or video analytics).
  
  

Other Prerequisites

• Proficiency in Python and deep learning frameworks (PyTorch strongly preferred; TensorFlow acceptable).
• Solid understanding of statistics and ML fundamentals (sampling, hypothesis testing, regularization, cross‑validation).
• Experience deploying models to production (batch and real-time) and monitoring performance.
• Hands-on with data versioning, experiment tracking, and model evaluation at scale.
• Experience with Azure ML, AKS, Azure Functions, Blob Storage, Event Hub.
• Knowledge of edge inference (NVIDIA Jetson, ONNX/TensorRT), or Triton Inference Server.
• Broader AI/ML skills (NLP, recommendation, time-series forecasting) and data analytics (SQL, BI).
• Familiarity with QA/QC for ML: bias/fairness checks, robustness testing, adversarial examples, test oracles for CV.
• Experience in hospitality/F&B/gaming use cases and privacy/compliance considerations.
  
  

Marina Bay Sands is committed to building a diverse, equitable and inclusive workforce, providing equal opportunities as we grow our talent base to match our growth ambitions in Singapore. Our employees are committed to adhere to and abide by all rules, regulations, policies and procedures, including the rules of conduct and business ethics of the Company.