Machine Learning Engineer - Large Language Models

Company:  Text Blaze
Location: San Francisco
Closing Date: 05/11/2024
Salary: £250 Per Annum
Hours: Full Time
Type: Permanent
Job Requirements / Description

(Full Time) Machine Learning Engineer - Large Language Models at Text Blaze (United States)

Machine Learning Engineer - Large Language Models

Text Blaze United States

Date Posted: 28 Apr, 2023

Work Location: San Francisco, United States

Salary Offered: $80000 — $150000 yearly

Job Type: Full Time

Experience Required: 3+ years

Remote Work: Yes

Stock Options: Yes

Vacancies: 1 available

We are looking for a talented Machine Learning Engineer with interest in training large language models to join our innovative and fast-paced team. In this role, you will work on cutting-edge NLP projects and play a crucial part in developing and refining our productivity tools. If you are passionate about machine learning, have a strong background in natural language processing, and thrive in a collaborative and high-impact environment, we'd love to hear from you!

Responsibilities:

  • Fine tune large language models that can generate high-quality text to solve domain specific needs.
  • Implement end-to-end machine learning pipelines, including data preprocessing, model training, evaluation, and deployment.
  • Continuously research and stay up-to-date with recent advancements in NLP and large language models, applying novel techniques and methodologies to improve our models.
  • Conduct experiments and benchmarking to assess the performance of various model architectures and optimize hyperparameters.
  • Troubleshoot and resolve any issues arising during model training and deployment.

Qualifications:

  • Bachelors or Masters in Computer Science, Mathematics, or a related field with a focus on machine learning and NLP.
  • Hands-on experience working with large language models like GPT, LLAMA, BERT, or Transformer-based architectures.
  • Proficiency in Python and deep learning frameworks such as TensorFlow or PyTorch.
  • Strong knowledge of NLP techniques, including tokenization, language modeling, and embeddings.
  • Experience with distributed training and optimization techniques for large-scale machine learning models.
  • Solid understanding of cloud platforms (e.g., GCP (preferred), AWS) and their machine learning offerings.
  • Strong analytical and problem-solving skills, with the ability to think creatively and propose innovative solutions.
  • Excellent communication skills and the ability to collaborate effectively in a cross-functional team.
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