Machine Learning Software Engineer

3 weeks ago


New York, New York, United States Moody's Full time

Job Summary

The Associate Director-Machine Learning Engineering will be responsible for developing cutting-edge software applications in generative AI and building innovative solutions that address the unique challenges faced by Moody's.

Key Responsibilities

  • Develop production grade generative AI solutions, with a focus on large language models, to develop novel methods and techniques that can be applied to Moody's challenges.
  • Collaborate with cross-functional teams to define objectives, identify data sources, assist data collection process, and develop production grade software applications.
  • Design, implement, and validate machine learning algorithms and models; optimize and productionize their performance for real-world applications.
  • Stay up to date with the latest developments in the field of generative AI and identify opportunities to apply state-of-the-art research to Moody's problems.
  • Contribute to the broader research community by publishing research in top-tier conferences and journals.
  • Mentor and provide guidance to junior researchers and data scientists.

Requirements

  • Master's degree in Computer Science, Machine Learning, Computer Engineering, relevant technical field, or equivalent practical experience.
  • Strong background in generative AI, with a focus on large language models and natural language processing.
  • Proficiency in Python, and experience with machine learning frameworks such as PyTorch or TensorFlow.
  • Experience building applications with Large Language Models (LLMs).
  • Knowledge of state-of-the-art machine learning techniques, including deep learning, reinforcement learning, and unsupervised learning.
  • Demonstrated ability to design, implement, and validate machine learning models for real-world applications.
  • Experience in the financial industry or credit risk modelling is a plus.

Moody's is an Equal Opportunity Employer

Moody's also provides reasonable accommodation to qualified individuals with disabilities or based on a sincerely held religious belief in accordance with applicable laws.



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