Staff ML Engineer, Fine Tuning

What you'll do

• Design and execute finetuning strategies for large language models and deep learning architectures tailored to Slack's NLP tasks.
• Manage the full model training lifecycle including data curation, infrastructure setup, hyperparameter optimization, and evaluation.
• Build and maintain scalable finetuning training pipelines on GPU infrastructure.
• Deploy and monitor machine learning models in production to serve millions of daily active users.
• Collaborate with product managers and designers to conceptualize and build new features for the platform.
• Mentor other engineers and perform high-quality code reviews to improve engineering standards and tooling.
• Lead technical architecture discussions and drive key technical decisions within the team.

What we're looking for

• Must have 5+ years of experience training and fine-tuning deep learning models in NLP or related domains.
• Must have 5+ years of experience with common deep learning frameworks such as PyTorch, TensorFlow, or JAX.
• Must have a track record of shipping fine-tuned models to production for real users at scale.
• Must be proficient in functional or imperative programming languages including Python, PHP, Ruby, Go, C, Scala, or Java.
• Must be able to lead technical architecture discussions and drive technical decisions within the team.
• Must possess strong communication skills to explain complex technical concepts to non-technical stakeholders.
• Ability to write understandable, testable code with a focus on maintainability.