Senior Machine Learning Engineer (R50026698)

Company:  Fox Corporation
Location: Los Angeles
Closing Date: 22/10/2024
Salary: £150 - £200 Per Annum
Hours: Full Time
Type: Permanent
Job Requirements / Description

OVERVIEW OF THE COMPANY

JOB DESCRIPTION

A SNAPSHOT OF YOUR RESPONSIBILITIES

  • Develop and fine-tune Large Language Models (LLMs) to meet specific product requirements.
  • Design and implement scalable machine learning pipelines for training and deploying LLMs.
  • Optimize LLMs for performance, efficiency, and accuracy in various applications.
  • Collaborate with data scientists, product managers, and software engineers to integrate LLMs into products.
  • Conduct thorough testing and validation of models to ensure robustness and reliability.
  • Continuously research and stay up-to-date with advancements in LLMs and related technologies.
  • Develop and document methodologies, findings, and best practices for LLM fine-tuning.
  • Mentor junior team members and contribute to a culture of continuous learning.
  • Participate in code reviews and ensure high coding standards within the team.
  • Engage in the full machine learning lifecycle, from data collection and preprocessing to model deployment and monitoring.

WHAT YOU WILL NEED

  • MSc or PhD in Computer Science, Data Science, Machine Learning, or a related field.
  • Industry experience in machine learning, with a focus on developing and fine-tuning language models.
  • Strong expertise in developing and fine-tuning LLMs, such as GPT, BERT, or similar models.
  • Proficiency in Python and experience with machine learning frameworks such as TensorFlow, PyTorch, or similar.
  • Experience with cloud services (AWS, GCP, Azure, Databricks) and ML infrastructure.
  • Strong understanding of software engineering principles and fundamentals, including data structures and algorithms.
  • Excellent problem-solving skills and ability to work in a collaborative team environment.
  • Strong communication skills, with the ability to distill complex technical concepts for various audiences.
  • Experience with embeddings, vectorization, and database optimization is a plus.
  • Familiarity with ethical considerations in AI and a commitment to developing responsible AI solutions.
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