Lead Analyst, AI Engineer (Data Science)

Overview

This role sits within a global product organization operating at the core of the semiconductor manufacturing ecosystem. As a Lead Analyst, AI Engineer, you will design, develop, and deploy advanced machine learning and deep learning solutions applied to real-world hardware and semiconductor manufacturing challenges. You will work closely with engineers, researchers, and product teams on production-grade AI systems that directly impact yield, quality, and process control at scale.

What you will do

• Design, develop, and optimize machine learning and deep learning models for semiconductor and hardware manufacturing use cases
• Build and prototype AI solutions using Python, NumPy, Pandas, and Scikit-learn
• Develop deep learning models using PyTorch or TensorFlow/Keras, including CNNs and transformer-based architectures
• Apply supervised and unsupervised learning techniques, feature engineering, model selection, and validation strategies
• Work on image processing and algorithm development for defect detection and process optimization
• Contribute to LLM-based solutions, including embeddings, fine-tuning, and retrieval-augmented generation (RAG) pipelines
• Collaborate with cross-functional engineering, product, and research teams to translate system requirements into AI solutions
• Participate in technical design discussions, code reviews, and performance optimization
  
  

• Minimum 5 years of hands-on experience in Python, machine learning, deep learning, algorithm development, and image processing
• 4+ years of practical experience with PyTorch and/or TensorFlow/Keras
• Strong understanding of ML concepts including feature engineering, regularization, cross-validation, and ensemble methods
• Experience with deep learning architectures such as CNNs, RNNs, LSTMs, Transformers, and attention mechanisms
• Exposure to LLMs, embeddings, vector databases (e.g. FAISS, Milvus, Pinecone), and prompt engineering
• Solid SQL fundamentals and experience working with data pipelines
• Proficiency with Git/GitHub, Jupyter notebooks, and basic Docker usage
• Mandatory background in product, semiconductor, or hardware manufacturing companies
• Educational background meeting one of the following:
• PhD with 2+ years of relevant experience
• Master’s degree with 5+ years of relevant experience
• Bachelor’s degree with 7+ years of relevant experience
  

• Work on complex, real-world AI problems with direct impact on physical systems and manufacturing outcomes
• High ownership role within an engineering-driven, innovation-focused environment
• Collaboration with senior engineers, researchers, and applied scientists
• Exposure to large-scale, production-grade AI and computer vision systems
• Hybrid working model supporting on-site collaboration and focused individual work
  
  

We believe strong sales organizations are built on diverse perspectives, experiences, and leadership styles. We are committed to fostering an inclusive environment where individuals are valued for their expertise, ideas, and contribution and where equitable opportunities for growth and advancement are part of how we build high-performing teams.