AI/ML Engineer

Keysight Technologies; Bayan Lepas; On-site; MYR 315,000 - 434,000; Full time

Job summary

A leading technology company in Penang, Malaysia is seeking an experienced AI/ML Engineer to innovate in PathWave Manufacturing Analytics (PMA). The role involves maintaining and scaling AI solutions, including chatbots and anomaly detection systems. Candidates should have a Master’s degree and over 4 years of experience in ML/AI with strong skills in Python and deep learning frameworks. The position offers opportunities to drive AI standardization and ensure production excellence.

Qualifications

• 4+ years of experience as a Data Scientist or Machine Learning Engineer.
• Experience with end-to-end ML/AI system deployment and monitoring.
• Proven expertise in using modern data science tools.

Responsibilities

• Own maintenance and scaling of AI services.
• Deploy PMA Solution Chatbot for user support.
• Implement Real‑Time Anomaly Detection for processes.
• Drive AI/ML standardization across teams.

Skills

Python

Deep learning frameworks (PyTorch/TensorFlow)

Data science stack (Pandas, NumPy, Jupyter)

Natural Language Processing

MLOps best practices

Education

Master’s degree in a related field

Tools

FastAPI

Jenkins

AWS

Job description

We are seeking an experienced AI/ML Engineer to join our team and drive the next phase of innovation for PathWave Manufacturing Analytics (PMA). This role is critical to sustaining and accelerating PMA’s AI capabilities by ensuring reliable production systems and advancing cutting-edge AI features.

This role demands a candidate who can independently move complex AI features from research/PoC into reliable, scalable production systems while maintaining code quality and operational excellence.

Responsibilities

• Own the production maintenance and scaling of the deployed User Guide Chatbot.
• Complete and deploy the PMA Solution Chatbot to enhance user support capabilities.
• Co‑own and improve the Auto‑Diagnose feature for predictive diagnostics.
• Implement and deploy Real‑Time Anomaly Detection for manufacturing processes.
• Advance the PMA Data Query Engine, enabling natural‑language access to manufacturing data.
• Lead feature‑usage analytics to optimize AI performance and adoption.
• Drive AI/ML standardization across PMA and DO teams for consistency and best practices.
• Bridge PoC‑to‑production gaps to ensure robust, scalable AI services.
• Promote efficiency and innovation within the PMA analytics platform.

Tech stack: Python, PyTorch/TensorFlow, Hugging Face, LangChain/LlamaIndex, open-source vector DBs, FastAPI/Flask, PostgreSQL/Snowflake, GPU inference, MLflow, and Jenkins CI/CD.

Qualifications

Education:

• Master’s degree or higher in Computer Science, Mathematics, Machine Learning, Artificial Intelligence, Natural Language Processing, or a closely related field

Professional Experience:

• 4+ years of hands‑on experience as a Data Scientist, Machine Learning Engineer, or Full‑Stack AI Engineer with end‑to‑end ML/AI system ownership. (from prototyping to production deployment and monitoring)

Core Technical Expertise:

• Advanced proficiency in Python and the modern data science stack (Pandas, NumPy, Jupyter)
• Deep experience with deep learning frameworks: PyTorch and/or TensorFlow/Keras
• Strong expertise in open‑source LLM ecosystems, including Hugging Face Transformers, PEFT, Accelerate, and vLLM/Llama.cpp
• Proven track record designing and implementing Retrieval‑Augmented Generation (RAG) pipelines, including chunking strategies, embedding models, vector stores, and reranking
• Solid understanding of advanced prompting techniques, chain‑of‑thought, tool calling, and Model Context Protocol (MCP) or similar agentic frameworks

Production & Deployment Skills:

• Experience building and serving production‑grade AI services with FastAPI, Flask, or similar frameworks
• Familiarity with MLOps best practices: experiment tracking (MLflow, Weights & Biases), model registry, CI/CD (Jenkins, GitHub Actions), and monitoring (Prometheus, Grafana, LangSmith)
• Hands‑on experience with GPU‑accelerated inference (TensorRT, ONNX, DeepSpeed) and scaling LLM workloads
• Working knowledge of cloud platforms, preferably AWS (SageMaker, Bedrock, ECS/EKS, Lambda) or Azure (Azure ML, OpenAI service, AKS)

Preferred Skills

• Experience with natural‑language‑to‑SQL/code generation or semantic search over manufacturing/engineering data
• Background in time‑series analysis and real‑time anomaly detection
• Contributions to open‑source projects or relevant publications are a strong plus