RAG Development: Enhance LLM performance with RAG methods.
Knowledge Management: Develop and maintain a knowledge management system. Inspection Support: Provide ML-based support for inspection services.
Data Engineering: Manage and preprocess datasets; develop pipelines.
Model Training: Train and optimize LLMs.
Data Security: Implement data security practices.
Research: Stay updated on NLP advancements.
Collaboration: Work with teams; communicate technical concepts.
Testing: Develop and execute testing protocols.
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Machine Learning Engineer (RAG - Open Source LLM)
We urgently seek a Machine Learning Engineer with expertise in retrieval-augmented generation (RAG) techniques. This role involves implementing a knowledge management system and supporting the company's inspection services.
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Education: Bachelor's/Master's in Computer Science, Data Science, Machine Learning, or related field; Ph.D. is a plus.
Experience: Proven experience in ML, NLP, data engineering, LLMs (e.g., GPT, BERT, T5), and data security. RAG experience is essential.
Technical Skills: Proficient in Python, ML libraries (TensorFlow, PyTorch), and data management tools (SQL, NoSQL, Hadoop).
Soft Skills: Strong problem-solving, communication, teamwork, and multitasking abilities.
Preferred:
Experience deploying ML models, familiarity with cloud platforms (AWS, Google Cloud, Azure), version control (Git).
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Working ModelFull Time
job categoryengineer
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