AI Engineer

A primary objective is to fine tune the models for semiconductor domain. This role requires practical understanding of semiconductor mathematical models, apply strong data engineering principles to analyse & predict behaviours, enable characteristics solutions in semiconductor space for process development and design rules. Expected to perform independently.

·       Fine Tune Modeling Techniques

·       Strong NLP experience

·       Good Understanding of Model Mathematics

·       Inference Optimization

·       LoRA/ QLoRA/ PEFT

·       Deep Neural Networks

·       Applied LLM Application Development in semiconductor domain

Bonus Skills:

·       Hands-on experience building applications using LangChain or LlamaIndex.

·       Expert Python & Pandas: Demonstrable mastery in using Python and the

Pandas library for complex data manipulation, cleaning, and analysis, especially with Excel filesAPI Development: Proven experience building and deploying production-ready APIs using FastAPI or Flask.

·       RAG Implementation: Practical knowledge and project experience in building RAG pipelines, including the use of vector databases (e.g., Qdrant, Chroma, FAISS).

·       Data Pipeline Skills: Experience in building reliable data ingestion (ETL) and processing workflows.

·       On-Premise Model Familiarity: Understanding of how to work with open-source LLMs (e.g., Llama, Mistral) in a local environment is a significant advantage

Qualification:

·       A minimum of 3-5 years of professional LLM development experience in Semiconductor domain.

·       2-4 years of direct, hands-on experience in AI/ML development, with a focus on applied AI and LLM applications in Semiconductor domain