
Data Engineer
6 days ago
Job Description
Role responsibilities
- Develop and optimize LLM models using state-of-the-art techniques, focusing on RAG (Retrieval-Augmented Generation).
- Implement content extraction methods to enhance the accuracy and relevance of generated responses.
- Collaborate with cross-functional teams to identify and address LLM development and deployment challenges.
- Stay updated with the latest advancements in natural language processing (NLP) and machine learning research.
- Provide technical guidance and mentorship to junior team members.
- Contribute to documenting and disseminating best practices in LLM development and deployment.
- Implement RPA solutions to automate repetitive tasks and improve operational efficiency.
- Collaborate with data scientists and business analysts to understand data requirements and translate them into technical solutions.
- Monitor performance, troubleshoot issues, and optimize data workflows for scalability and reliability
- Stay up-to-date with the latest trends and technologies in data engineering, RPA, and AI/ML
Required Skill Sets:
- Bachelors or higher degree in Computer Science, Engineering, or a related field.
- Proven experience in developing and fine-tuning LLM models, preferably with a focus on RAG.
- Hands-on experience with RPA tools such as UiPath, Automation Anywhere, Blue Prism, Power Automate
- Strong proficiency in Python programming and familiarity with relevant libraries/frameworks such as TensorFlow, PyTorch, scikit-learn.
- Solid understanding of natural language processing (NLP) fundamentals and machine learning principles.
- Experience with content extraction techniques such as Named Entity Recognition (NER), text summarization, and information retrieval.
- Familiarity with the concept of local LLMs and their applications in specific domains or languages.
- Excellent problem-solving skills and the ability to work effectively in a collaborative team environment.
- Strong communication skills with the ability to explain complex technical concepts to non-technical stakeholders
Preferred Qualifications:
- Experience with cloud platforms such as AWS, Azure, or Google Cloud
- Prior working knowledge in implementing RPA and AI/ ML Methods.
- Certification in RPA or AI/ML technologies.
- Contributions to open-source projects related to natural language processing or machine learning.
- Knowledge of big data technologies (e.g., Hadoop, Spark, Kafka)
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