Senior Machine Learning Engineer

1 day ago

Bishan, Singapore CDG ZIG Full time

Job Responsibilities:

  • Architect, develop, and deploy end-to-end machine learning models to solve business problems in areas such as forecasting, recommendation, NLP, or computer vision.
  • Conduct in-depth exploratory data analysis (EDA), perform sophisticated feature engineering, and collaborate with data engineers to build robust data preprocessing pipelines.
  • Lead the prototyping and experimentation of novel algorithms, rigorously testing hypotheses and evaluating model performance against key business metrics.
  • Write clean, scalable, and production-ready code (primarily Python) for model training, inference, and integration via APIs.
  • Take full ownership of the ML model lifecycle, including versioning, monitoring for performance degradation or drift, and implementing automated retraining workflows.
  • Collaborate with MLOps and software engineers to seamlessly integrate ML models into our production applications and services.
  • Clearly articulate complex findings, model behaviors, and performance metrics to both technical and non-technical stakeholders.
  • Any ad hoc duties as assigned

Job Requirements:

  • Bachelor's or master's degree in computer science, Statistics, Mathematics, or a related quantitative field is preferred.
  • Minimum 5 years of relevant experiences preferred
  • Deep understanding of machine learning theory, algorithms (e.g., regression, classification, clustering), and statistical principles.
  • Expert proficiency in Python and its data science ecosystem (Pandas, NumPy, Scikit-learn, Matplotlib).
  • Extensive hands-on experience with at least one major deep learning framework, such as TensorFlow, PyTorch, or JAX.
  • Strong SQL skills and experience working with large-scale datasets from data warehouses or data lakes.
  • Proven experience in building and deploying ML models in a commercial environment using a major cloud platform (AWS, GCP, or Azure).
  • Solid software engineering fundamentals, including object-oriented design, version control (Git), testing, and writing maintainable code.
  • Familiarity with MLOps principles and tools (e.g., MLflow, DVC, Kubeflow) for experiment tracking and model management.
  • Experience in building solutions using Generative AI models and frameworks (e.g., LangChain, LlamaIndex) is a significant plus.
  • Direct experience in the ride-hailing industry and a strong understanding of dynamic pricing models would be a significant advantage.
  • Proactive and analytical approach to problem-solving, with a keen eye for detail.
  • Strong ownership mindset with the ability to work independently and drive projects from concept to production.
  • Excellent ability to translate complex technical concepts into clear business context for stakeholders.

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