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6-9 Years
SGD 7,000 - 10,000 per month
Early Applicant
  • Posted a day ago
  • Be among the first 10 applicants

Job Description

Responsibilities

  • Develop, test and deploy ML, NLP, Generative BI, GenAI and AI-assisted automation solutions for enterprise environments.

  • Prepare data, perform feature engineering, train models and develop prompts, RAG pipelines and Agentic AI workflows.

  • Implement evaluation frameworks covering accuracy, groundedness, latency, robustness, safety and business acceptance criteria.

  • Integrate ML models and LLM/AI services with enterprise data platforms, semantic layers, APIs, BI and visualization tools.

  • Build reproducible MLOps pipelines for model packaging, deployment, monitoring, retraining and production lifecycle management.

  • Implement logging, explainability, human-in-the-loop review, security, privacy, governance and audit controls.

  • Support SIT/UAT, unit testing, defect resolution, production deployment, technical documentation, evaluation evidence and operational runbooks.

Requirements

  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science or a related technical discipline.

  • 6-9 years of experience in AI/ML, analytics or software engineering, with substantial hands-on experience delivering enterprise AI solutions.

  • Strong programming and ML expertise in Python, Spark, TensorFlow/PyTorch, scikit-learn, MLflow and modern LLM/Agent frameworks.

  • Hands-on experience with RAG, embeddings, vector search, prompt engineering, LLMs, Agentic AI, feature engineering and model/LLM evaluation.

  • Experience with APIs, containers, Kubernetes, cloud AI/ML services, Git, CI/CD, monitoring and production deployment practices.

  • Knowledge of responsible AI, model governance, data privacy, explainability and human-in-the-loop processes, preferably within banking, risk, AML, payments or customer analytics.

  • Strong ownership, analytical thinking, collaboration skills, with the ability to work independently, participate in peer reviews and deliver high-quality, traceable and production-ready solutions relevant cloud AI/ML or Databricks certification is preferred.

More Info

Key Skills

vector search

RAG embeddings

human-in-the-loop review

scikit-learn

MLflow

explainability

LLMs

LLM Agent frameworks

cloud AI ML services

MLOps pipelines

prompt engineering

Agentic AI

CI/CD

feature engineering

audit controls

Containers

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