GenAI & Classical ML Engineer — Industrial Analytics

Keysight Technologies SAles Spain SL.

Singapore

In loco

SGD 120.000 - 180.000

Tempo pieno

14 giorni+
Generatore di candidature

Una candidatura fatta su misura per questo lavoro — un curriculum e una lettera di presentazione personalizzati, perfettamente in linea con l'annuncio.

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Descrizione del lavoro

Keysight Technologies is seeking an experienced AI/ML Engineer to lead end-to-end development of advanced AI/ML solutions for analytics in manufacturing and semiconductor sectors. The role emphasizes production-grade systems, anomaly detection, predictive maintenance and market intelligence using classical ML and GenAI capabilities.

You will own architectures, data pipelines, and customer-facing GenAI tools, collaborating with MLOps, data engineering, and product teams in a fast-paced Agile

Competenze

  • Master’s degree in ML/CS or related field.
  • 4+ years of professional ML/AI engineering experience with end-to-end deployment.
  • Strong Python, ML/DL, and NLP expertise.
  • Experience with GenAI, RAG, and vector databases.

Mansioni

  • Architect unified AI/ML capabilities integrating classical ML with Generative AI platforms (AWS Bedrock).
  • Design robust anomaly detection and predictive maintenance systems.
  • Build and scale RAG pipelines and agentic workflows for test plan generation.
  • Develop summarization and information extraction pipelines for market intelligence.

Conoscenze

Python
MLOps
NLP
RAG architectures
Git & CI/CD
AWS Bedrock
LangChain
Prompt engineering
Data pipelines

Formazione

Master's degree

Strumenti

Scikit-learn
XGBoost
TensorFlow
PyTorch
Apache Spark
LangChain

Descrizione del lavoro

Keysight Technologies is seeking an experienced AI/ML Engineer to lead end-to-end development of advanced AI/ML solutions for analytics in manufacturing and semiconductor sectors. The role emphasizes production-grade systems, anomaly detection, predictive maintenance and market intelligence using classical ML and GenAI capabilities.

You will own architectures, data pipelines, and customer-facing GenAI tools, collaborating with MLOps, data engineering, and product teams in a fast-paced Agile

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