The Staff Machine Learning Engineer at Slack will focus on designing, training, and deploying NLP models that enhance core product experiences. This hands-on role requires deep expertise in model training and finetuning, with a strong emphasis on delivering business value through practical machine learning solutions. The engineer will work closely with cross-functional teams to conceptualize and build features for a large user base. The position demands a commitment to the full lifecycle of model training, from experimentation to production.

• 5+ years of hands-on experience training and fine-tuning deep learning models in NLP or a closely related domain.
• 5+ years of experience with common deep learning frameworks like PyTorch, TensorFlow, or JAX.
• A track record of shipping fine-tuned models to production that serve real users at scale.
• Experience with functional or imperative programming languages such as PHP, Python, Ruby, Go, C, Scala, or Java.
• Strong communication skills and the ability to explain complex technical concepts to non-technical stakeholders.

• Design and execute finetuning strategies for large language models tailored to Slack's NLP tasks.
• Own the model training lifecycle end-to-end, including data curation, training infrastructure, and deployment.
• Build and maintain scalable finetuning training pipelines on GPU infrastructure.
• Collaborate with Product Managers, Designers, and Frontend Engineers to conceptualize and build new features.
• Mentor other engineers and contribute to large multi-functional projects that impact the business.

• Employees at Slack, as part of Salesforce, are often offered comprehensive benefits focused on wellbeing and inclusion, including competitive health-care coverage, time off to rest, recharge and volunteer, and holistic programs that support mental health, family planning and overall work–life balance.