| Python NLP and LLM developer Location: Remote -Hybrid in San Jose, California Experience: 8+ years Client: IOPEX Technologies - Cisco Visa: Any Independent candidates Duration: Long term co at California, Maryland, USA |
| Email: [email protected] |
| From: Bharath Kumar, oncorre [email protected] Reply to: [email protected] Role: Python NLP and LLM developer Location: Remote / Hybrid in San Jose, California Experience: 8+ years Client: IOPEX Technologies / CiscoVisa: Any Independent candidates Duration: Long term contract Summary: We are seeking a talented and experienced Python NLP and LLM developer to join our team. The ideal candidate will have a strong understanding of natural language processing and machine learning, as well as experience integrating with large language models and deploying it as an API. Responsibilities: Develop and implement state-of-the-art NLP and LLM solutions. Design , engineer and evaluate NLP pre-processing, model training and inference pipelines. Integrate with LLMs like OpenAI for implementing retrieval augmented generation, synthetic content generation, creating abstractive summaries etc. Ability to benchmark and evaluate multiple models. Evaluate and improve NLP and LLM performance. Collaborate with data scientists and ML engineers to develop and deploy NLP and LLM solutions. Qualifications: Bachelor's/Master's degree in Computer Science, Artificial Intelligence, Natural Language Processing, or a related field. 2+ years of experience developing NLP models, Predictive AI Solutions. Experience developing NLP applications such as machine translation, text summarization, and question answering. Strong understanding of natural language processing, machine learning and Deep learning algorithms. Excellent Experience with Python and working with Jupyter notebooks. Experience working with NLP libraries like Spacy / PyTorch. Experience with Git, CI/CD and Linux environments. Experience working with Agile development teams. Excellent communication and collaboration skills. Bonus Qualifications: Experience with deep learning architectures such as RNNs, CNNs, and Transformers. Experience with transfer learning and fine-tuning of large language model. Keywords: continuous integration continuous deployment artificial intelligence machine learning information technology |
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| Thu Dec 28 20:41:00 UTC 2023 |