6 hours ago
Singapore, SingaporeSenior
Responsibilities
- Lead the architecture and continuous improvement of AI/ML capabilities integrating classical ML with Generative AI platforms, primarily AWS Bedrock.
- Build anomaly detection and predictive maintenance systems using XGBoost and Scikit-learn on real-time sensor and test data.
- Develop RAG pipelines and agentic workflows for automated manufacturing test-plan generation and other high-precision applications.
- Create summarization and information-extraction pipelines for large collections of news articles, press releases, and open-source intelligence.
- Own a customer-facing GenAI Q&A chatbot focused on semiconductor manufacturing risks, sensor measurements, and test plans.
- Solve regression, classification, clustering, and time-series forecasting problems and integrate them with GenAI components where appropriate.
- Apply RNNs, LSTMs, and modern LLM methods to operational logs, market reports, and competitor pricing data.
- Collaborate with MLOps, data engineering, domain, and product teams on validation, observability, versioning, and automated testing.
- Perform model evaluation, hyperparameter tuning, feature engineering, bias and risk assessment, drift monitoring, and ethical AI practices.
- Contribute to large-scale data pipeline enhancements using Apache Spark, vector databases, and distributed processing patterns.
Requirements
- Master's degree in Machine Learning, Computer Science, Data Science, Statistics, Quantitative Mathematics, or a closely related field.
- At least 4 years of professional experience as a Machine Learning Engineer, AI Engineer, or equivalent.
- Proven ownership of end-to-end development, validation, and production deployment of classical ML and GenAI/LLM-based systems.
- Strong hands-on experience with Scikit-learn, XGBoost, TensorFlow or PyTorch, and RNNs/LSTMs.
- Experience building RAG architectures, prompt-engineering systems, curated knowledge bases, optimized vector databases, hybrid search, and agentic workflows.
- Experience with LangChain, LangGraph, CrewAI, Bedrock Agents, or equivalent technologies.
- Production-grade Python experience, clean-code practices, Git, testing, CI/CD, and MLOps practices including model monitoring, drift detection, and automated retraining.
- Solid experience with AWS Bedrock, including Knowledge Bases, custom models, and Lambda/Step Functions orchestration, or comparable Generative AI platforms.
- Familiarity with Agile/Scrum, cross-functional delivery, rigorous ML/GenAI validation, evaluation metrics, and bias/risk assessment.
- Fluency in English, including technical terminology.
- Preferred experience in manufacturing, semiconductors, sensor-based analytics, test and measurement instrumentation, or industrial risk analytics.
- Preferred hands-on Apache Spark experience, hybrid classical ML and GenAI pipelines, production-impactful AI/ML projects, and Model Context Protocol integrations.
Tech Stack
Categories
About Keysight
Keysight Technologies builds electronic test and measurement instruments and software used for design, validation, and manufacturing by engineers in communications, semiconductor, aerospace and defense, automotive, and data center markets. Its portfolio includes oscilloscopes, signal and network analyzers, RF/microwave test systems, and EDA and network test software, sold with services and support. Founded in 2014 as a spin-off from Agilent Technologies, Keysight is a public company (NYSE: KEYS) headquartered in Santa Rosa, California.