The Role
The role involves designing and optimizing RAG pipelines, developing datasets, evaluating LLM applications, and deploying AI applications while collaborating with cross-functional teams.
Summary Generated by Built In
Job Summary & Responsibilities
- Design, implement, test, and continuously optimize end-to-end RAG pipelines, including data parsing, ingestion, prompt engineering, and chunking strategies.
- Curate and develop high-quality datasets, using synthetic data generation for robust training and evaluation.
- Rigorously evaluate LLM applications on various metrics including correctness, latency, and hallucination.
- Assist in the deployment of LLM-based applications, analyze user feedback, and contribute to iterative improvements.
- Write clean, maintainable, and testable code following best practices.
- Collaborate with cross-functional teams to integrate AI components into other systems.
- Master or Ph.D. in Computer Science, Machine Learning, or a related field and a minimum of 2 years of hands-on industry experience in software engineering.
- Expertise and intensive hands-on experience in LLM/RAG development.
- Strong skills in Python framework SentenceTransformers and data analysis libraries (Pandas, NumPy).
- Hands-on experience with vector databases (e.g., Chroma) and RAG evaluation frameworks.
- Strong communication and presentation skills.
Top Skills
Chroma
Numpy
Pandas
Python
Sentencetransformers
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The Company
What We Do
For over a half-century, Advantest has been designing innovative electronic measuring equipment and semiconductor test systems essential to the development and manufacture of advanced computer and telecommunications products. On April 1, 2012, Advantest completed its integration of Verigy Ltd.
Additional Information about Advantest can be found at www.advantest.com.
