Natural Language Processing Engineer

Company:  Servient, Inc
Location: Houston
Closing Date: 02/11/2024
Hours: Full Time
Type: Permanent
Job Requirements / Description

At Servient, we're building Generative AI powered LegalTech. We're looking for a talented and motivated Large Language Model Developer to join our dynamic team and fine-tune and serve cutting-edge LLMs to bring efficiency to legal tasks. You'll be instrumental in optimizing these models for fine tuning and scalable inference capabilities on GPUs.


Responsibilities:

  • Design and implement NLP algorithms to work in conjunction with LLMs to analyze large legal documents, help legal professionals find evidence quickly and organize their evidence.
  • Collaborate with legal professionals to understand their workflows and come up with creative solutions to bring efficiency to these tasks
  • Develop custom training pipelines for utilizing the power of GPUs in LLM for inference.
  • Define and monitor various evaluation metrics for the NLP algorithms and continuously iterate to improve them.
  • Collaborate with NLP scientists, AI engineers, software developers to integrate LLMs into our products for legal tasks.
  • Stay up-to-date on the latest advancements in LLM research and development, actively contribute to knowledge sharing within the team.


Qualifications:

The ideal candidate should have 1-4 years of experience with a

  • Strong understanding of Natural Language Processing (NLP) concepts and techniques, including deep learning models for language generation.
  • Experience with supervised and unsupervised learning methodologies as applied to Natural language documents
  • Expertise in deep learning frameworks (e.g., TensorFlow, PyTorch) and scikit-learn
  • Excellent software development skills with a focus on code quality, performance optimization, and maintainability.
  • Strong communication and collaboration skills, with the ability to work effectively in a fast-paced, research-oriented environment.


Nice to have:

  • Experience in distributed computing and scaling machine learning models for production environments.
  • A keen understanding of NLP applications in your specific field of interest (e.g., healthcare, education, finance).

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