Design develop and implement advanced LLM applications using stateoftheart models and techniques.
Lead research initiatives in RetrievalAugmented Generation (RAG) systems improving the accuracy and efficiency of information retrieval and generation.
Conduct experiments on training and finetuning large language models for specific domains and tasks.
Collaborate with crossfunctional teams to integrate LLM solutions into production systems.
Stay uptodate with the latest advancements in LLMs NLP and deep learning and apply new techniques to ongoing projects.
Mentor junior team members and contribute to the overall growth of the AI research team.
Publish research findings in toptier conferences and journals.
Requirements:
2 years of experience in NLP deep learning and building LLM applications.
Strong programming skills in Python with experience in deep learning frameworks such as PyTorch or TensorFlow.
Extensive experience with transformerbased models (e.g. BERT GPT T5) and their applications.
Demonstrated expertise in developing RAG systems and improving their performance.
Proficiency in training and finetuning large language models including techniques like fewshot learning and prompt engineering.
Strong background in NLP techniques including text preprocessing tokenization and embedding methods.
Familiarity with MLOps practices and tools for model versioning experiment tracking and deployment.
Excellent problemsolving skills and ability to think creatively about AI solutions.
Strong communication skills and ability to explain complex technical concepts to both technical and nontechnical audiences.
IMMEDIATE JOINERS ONLY NEED APPLY.
Preferred Qualifications:
Experience with efficient training techniques for large models such as distributed training and mixedprecision training.
Knowledge of model compression techniques including quantization and distillation.
Familiarity with ethical AI practices and bias mitigation in language models.
Experience with multimodal models combining text with other data types (e.g. images audio).
Contributions to opensource NLP or LLM projects.
Good to have Publication record in toptier AI conferences (e.g. NeurIPS ICML ACL EMNLP).
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If youre passionate about advancing the field of large language models and have a track record of building innovative AI solutions wed love to hear from you. Join us in shaping the future of AI in ERP industry
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