JAD CONNECT SERVICES
Senior AI/ML Engineer
Skills
2 months ago
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Important information
Contract type:
Permanent
Salary:
MYR 180,000 – MYR 264,000 / year
Location:
Kuala Selangor, Selangor, Malaysia
Work mode:
Hybrid
Published on:
24 August 2026
What they need
About the role
We are looking for an AI / ML Engineer to build practical, production-ready AI and machine learning solutions for a healthcare technology platform. The role will work closely with Data Engineering, Product, Operations, and business stakeholders to turn real business problems into reliable AI/ML solutions. This includes classical ML, LLM-based tools, document AI, retrieval-augmented generation, workflow automation, and model deployment.
Key responsibilities :
- Build, test, and deploy AI/ML solutions that solve real healthcare, operational, and business problems
- Work with Python, SQL, PySpark, Delta Lake, and cloud-based data pipelines
- Develop LLM and applied AI solutions such as internal assistants, document processing, summarisation, classification, and RAG workflows
- Evaluate model quality using proper test sets, error analysis, and business acceptance criteria
- Work with data engineers to use trusted lakehouse datasets and support production ML/AI pipelines
- Monitor deployed models for quality, drift, reliability, cost, and business impact
- Document model assumptions, limitations, risks, and data dependencies
- Communicate clearly with both technical and non-technical stakeholders
Preferred skill sets:
- Strong Python, SQL, and PySpark skills
- Experience working with Delta Lake, lakehouse-style platforms, or cloud-based data platforms
- Experience with machine learning libraries such as scikit-learn, PyTorch, TensorFlow, pandas, or NumPy
- Experience building and evaluating ML models using real-world data
- Familiarity with LLMs, embeddings, vector search, RAG, or applied generative AI
- Good understanding of data quality, model evaluation, and production failure modes
- Good written and spoken English
- Strong hands-on experience with Azure Databricks
- Experience with MLflow, Databricks Workflows, Unity Catalog, or production ML pipelines on Databricks
- Experience designing agentic AI workflows, including tool-calling, workflow orchestration, human-in-the-loop review, evaluation, monitoring, and guardrails for safe production use
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