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Senior AI & ML Engineer

Singapore, Singapore
Contract
Posted Today
Mid-Senior level
On-site
AIMLData ScienceInformation TechnologyIT Services and IT Consulting, Financial Services, and Banking

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Job Description

We are looking for highly skilled and experienced professionals for the role of Senior Data Engineer / Senior AI & ML Engineer with strong expertise in enterprise data platforms, artificial intelligence, machine learning, and large-scale analytics solutions. The ideal candidate should possess deep technical knowledge in modern data engineering and AI/ML ecosystems, along with experience delivering scalable and secure solutions for government or public sector programs.

The role requires hands-on engineering expertise, architecture understanding, and the ability to work across complex data transformation and AI-driven initiatives.


Key Responsibilities

Data Engineering Responsibilities

  • Design, develop, and maintain scalable data pipelines and enterprise data platforms.
  • Build robust ETL/ELT frameworks for structured and unstructured data processing.
  • Develop and optimize data ingestion, transformation, and integration workflows.
  • Implement data lakes, data warehouses, and real-time streaming architectures.
  • Ensure data quality, governance, security, lineage, and compliance standards.
  • Work with large-scale datasets from multiple enterprise and government systems.
  • Optimize data storage, processing performance, and scalability.

AI/ML Responsibilities

  • Design, develop, train, and deploy machine learning and AI models for enterprise use cases.
  • Build predictive analytics, NLP, computer vision, recommendation systems, or intelligent automation solutions.
  • Implement MLOps practices for model deployment, monitoring, retraining, and governance.
  • Collaborate with business and domain teams to translate requirements into AI-driven solutions.
  • Evaluate emerging AI technologies and recommend modernization strategies.
  • Develop responsible AI frameworks aligned with governance and compliance requirements.

General Responsibilities

  • Collaborate with architects, business teams, analysts, and engineering teams.
  • Provide technical leadership and mentoring to junior engineers and data scientists.
  • Participate in architecture discussions, code reviews, and technical governance.
  • Support cloud migration, modernization, and digital transformation initiatives.
  • Prepare technical documentation, solution designs, and implementation plans.
  • Ensure adherence to security, privacy, and regulatory compliance standards.


Job Requirements:

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or related field.
  • 8+ years of hands-on experience in Data Engineering and AI/ML practices.
  • Data Engineering- Strong expertise in:
  • Python
  • SQL
  • Spark / PySpark
  • Hadoop ecosystem
  • ETL/ELT pipelines
  • Data Warehousing concepts
  • Experience with:
  • Apache Kafka
  • Airflow
  • Databricks
  • Snowflake
  • Big Data technologies
  • Strong knowledge of batch and real-time data processing.


  • AI/ML Engineering: Hands-on experience in:
  • Machine Learning algorithms
  • Deep Learning frameworks
  • NLP and Generative AI concepts
  • Model training and deployment
  • Experience with:
  • TensorFlow / PyTorch / Scikit-learn
  • ML pipelines and MLOps frameworks
  • Model monitoring and optimization
  • Understanding of AI governance, explainability, and responsible AI practices.

Cloud & DevOps

  • Experience with cloud platforms such as:
  • AWS
  • Azure
  • GCP
  • Knowledge of:
  • Docker
  • Kubernetes
  • CI/CD pipelines
  • Infrastructure automation

Government/Public Sector Experience (Preferred)

  • Experience working on Government/Public Sector digital transformation projects.
  • Understanding of governance, compliance, security, and large-scale citizen data systems.
  • Exposure to smart governance, public administration, e-governance, or national-scale platforms is an advantage.


Preferred Skills

  • Experience with GenAI, LLMs, Retrieval-Augmented Generation (RAG), or AI copilots.
  • Familiarity with graph databases and knowledge graphs.
  • Exposure to data governance and metadata management tools.
  • Experience with BI and analytics platforms such as Power BI or Tableau.
  • Certifications in Cloud, Data Engineering, or AI/ML are preferred.
Source: LinkedIn
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