Principal Data Scientist, TPG
Core
Architecting and delivering production AI, machine learning, and agentic systems to solve hard semiconductor engineering problems.
Role type
Principal/Lead Applied AI and Agentic Systems Engineer
Builds
Production AI systems, data pipelines, inference services, and agentic workflows for semiconductor engineering
Domain
Semiconductor industry + Applied AI/ML engineering
Deliverable
production ML models | product features
Required skills
Machine learning, statistical modeling, software engineering, cloud deployment, agentic AI, Python, PyTorch, TensorFlow, scikit-learn, XGBoost, model evaluation, CI/CD, API design
Preferred skills
People leadership, semiconductor domain knowledge, cloud platforms (AWS/GCP/Azure), Kubernetes, Docker, LLMs, RAG, agentic workflows, MCP tool integration
Technologies
PyTorch, TensorFlow, scikit-learn, XGBoost, AWS, GCP, Azure, Kubernetes, OpenShift, Docker
Responsibilities
Set architecture and technical direction for applied AI/ML/agentic AI; Design end-to-end systems (pipelines, features, models, inference, monitoring); Build models for prediction, diagnosis, optimization, and decision support; Ship agentic AI for analysis, knowledge retrieval, and automation; Define guardrails and evaluations for agentic AI; Break wide-open challenges into roadmaps and report progress to engineers and executives
Seniority
Principal/Lead, hands-on IC with people leadership
