Staff ML Engineer, Fine Tuning - Slack

Slack is seeking a Staff Machine Learning Engineer to lead fine-tuning of large language models for NLP tasks including summarization and search ranking. This role involves building scalable training pipelines and owning the full model lifecycle from experiment to production. The team delivers practical ML solutions that serve millions of daily active users.

• Design and execute finetuning strategies for large language models and other deep learning architectures tailored to Slack's NLP tasks (summarization, ranking, classification, generation).
• Own the model training lifecycle end-to-end: data curation, training infrastructure, hyperparameter optimization, evaluation, deployment and monitoring.
• Build and maintain scalable finetuning training pipelines on GPU infrastructure.
• Brainstorm with Product Managers, Designers and Frontend Engineers to conceptualize and build new features for our large user base.
• Produce high-quality results by leading or contributing heavily to large multi-functional projects.
• Mentor other engineers and deeply review code.
• Improve engineering standards, tooling, and processes.

• 5+ years of hands-on experience training and fine-tuning deep learning models in NLP or closely related domain.
• 5+ years of experience with common deep learning frameworks like PyTorch, TensorFlow, JAX, etc.