Job Description

About the Role:

The Safety ML team is hiring a Machine Learning Engineer to build and iterate on the next generation of safety systems at Reddit. In this pivotal role, you will be responsible for developing, training, and optimizing state-of-the-art large language models (LLMs) in order to scalably and efficiently support the enforcement of Reddit Rules. You will be partnering closely with other Safety teams (Operations, Engineering, Product, Data Science) at Reddit to identify and build solutions that will help keep users safe as Reddit grows.

Responsibilities:

• Design, develop, optimize and deploy ML models, including large language models, for various natural language processing tasks.
• Implement and maintain training pipelines, leveraging distributed training and optimizing for performance and efficiency.
• Collaborate with cross-functional teams to gather requirements, define model architectures and iterate on model development.
• Conduct model evaluations, performance analysis, and optimization to improve model accuracy and reduce biases.
• Stay up-to-date with the latest research and advancements in the field of natural language processing, multimodal signals, and large language models.
• Contribute to the development of best practices, guidelines, and ethical AI principles for responsible ML development and deployment.

Required Qualifications:

• 5+ years of relevant MLE experience in natural language processing, deep learning, and AI model development.
• Strong background in Python programming and deep learning frameworks like TensorFlow, PyTorch, or Hugging Face Transformers.
• Expertise in distributed training frameworks (e.g., Ray Training, PyTorch Distributed), and efficient utilization of hardware resources.
• Proficiency in data preprocessing, tokenization, embeddings, and language modeling techniques.
• Passion for developing scalable, well-designed, and responsible AI solutions that positively impact society.
• Excellent communication and collaboration skills, with the ability to discuss complex technical topics with diverse teams.
• Entrepreneurial spirit, self-motivation, and a bias towards action in fast-paced environments.

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