Lead Analyst, AI Engineer (Data Science)
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Job Summary
About the role
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
Requirements
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
Masters degree with 5 years of relevant experience
Bachelors degree with 7 years of relevant experience
Benefits
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
Diversity & Inclusion
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.
Key Skills
- Data Analytics
- Microsoft Access
- SQL
- Power BI
- R
- Data Visualization
- Tableau
- Data Management
- Data Mining
- SAS
- Data Analysis Skills
- Analytics
About Company
Bringing a personalized approach to connecting exceptional talent with unique opportunities. Specializing in recruitment for diverse roles, leveraging extensive experience and innovative strategies to find the perfect match for any business needs. Collaboration builds a stronger, mor ... View more
