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 (and growing!) user base
Produce high-quality results by leading or contributing heavily to large multi-functional projects that have a significant impact on the business
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 a closely related domain like speech, IR, or multimodal)
5+ years of experience with common deep learning frameworks like PyTorch, TensorFlow, JAX, etc
Track record of shipping fine-tuned models to production that serve real users at scale — not just research prototypes
Experience with functional or imperative programming languages: PHP, Python, Ruby, Go, C, Scala or Java
An analytical and data driven mindset, and know how to measure success with complicated ML/AI products
Led technical architecture discussions and helped drive technical decisions within the team
The ability to write understandable, testable code with an eye towards maintainability
Strong communication skills and you are capable of explaining complex technical concepts to designers, support, and other specialists.

Staff ML Engineer, Fine Tuning

Key skills