ML & AI Engineer

OPTIMUM SOLUTIONS (SINGAPORE) PTE LTD; Singapore; On-site; SGD 120,000 - 190,000; Full time

Job summary

OPTIMUM SOLUTIONS (SINGAPORE) PTE LTD is seeking a senior AI/ML Engineer to design, implement and deploy enterprise AI solutions. You will build end-to-end ML pipelines, work with LLM/Agent frameworks, and ensure rigorous evaluation and governance throughout production deployments.

You will prepare data, engineer features, train models, and develop prompts and workflows for RAG pipelines. Strong programming in Python and ML tooling is essential, with experience in cloud services and container

Qualifications

• 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, peer reviews and deliver production-ready solutions; relevant cloud AI/ML or Databricks certification is preferred.

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.

Skills

Python

Spark

TensorFlow/PyTorch

scikit-learn

MLflow

LLM/Agent frameworks

RAG

Embeddings

Vector search

Prompt engineering

APIs

Kubernetes

Cloud AI/ML services

Git

CI/CD

Monitoring

Production deployment

Responsible AI

Explainability

Human-in-the-loop

Databricks

Education

Bachelor’s or Master’s degree in CS/AI/ML/Data Science

Tools

Databricks

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.