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Upwork Anywhere

Natural Language Processing and Large Language Models Developer | New York, NY, USA

Non-disclosed

Join a dynamic team of innovative scientists, technologists, and scholars dedicated to transcending conventional methods. We aim to address intricate economic challenges and improve on alpha using the cutting-edge techniques of Natural Language Processing and Large Language Models

Position Overview:

Looking for visionary NLP and LLM focused scientists to harness the power of language to decode complex financial problems and manage vast volumes of textual data.

Key Responsibilities:
• Develop, and transition from concept to a functional prototype and final NLP or LLM product.
• Immerse yourself in a research-oriented environment, where you'll craft code, experiment with advanced NLP and LLM tools, and refine techniques to extract insights from financial narratives.
• Collaborate closely with various teams within our organization to seamlessly integrate your linguistic intelligence solutions into our products.
• Stay connected to the broader linguistic research community by fostering partnerships both internally and externally, and making a mark at relevant conferences.

Qualifications & Experience:

• Earned an advanced degree in Computer Science, Linguistics, Engineering, or another relevant field with an emphasis on NLP and LLM.
• Strong programming proficiency in languages such as Python, C++, Tensorflow, PyTorch, or similar.
• Past roles or internships centered around NLP, LLM, or related linguistic computational models.
• A foundation in language models, especially concerning extensive and multifaceted textual datasets, and an interest in applying these to financial challenges.
• Credible research contributions, preferably with publications in esteemed platforms focused on NLP or LLM such as ACL, EMNLP, or similar.
• Familiarity with cloud ecosystems and managing multi-machine configurations.
• Active involvement in the open-source linguistic community.

Location: New York, NY

Posted: Aug. 28, 2024, 10:35 p.m.

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