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
Solid proficiency in Python programming and familiarity with relevant libraries/frameworks such as Tensor Flow, 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 cooperative team setting.
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)

📌 Data Engineer Rpa & Ai/ml Expertise Kolkata (India)
🏢 SUN DEW SOLUTIONS PRIVATE
📍 India