Staff ML Engineer, Fine Tuning - Slack

Location: Seattle, WA, Atlanta, GA, San Francisco, CA | Type: Full-time

About the role

Slack is seeking a Staff Machine Learning Engineer to join their ML team, focusing on designing, training, and deploying NLP models that enhance core product experiences. The role emphasizes hands-on involvement in the full lifecycle of model training, from data curation to production deployment. This position is ideal for engineers who thrive in practical applications of machine learning rather than research-focused environments.

Responsibilities

• Design and execute finetuning strategies for large language models and deep learning architectures tailored to Slack's NLP tasks.
• Own the model training lifecycle end-to-end, including data curation, training infrastructure, hyperparameter optimization, evaluation, deployment, and monitoring.
• 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 conduct thorough code reviews.

Requirements

• 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.

Benefits

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.
• Holistic programs that support mental health, family planning, and overall work–life balance.

Pay

$197,300 - $344,700 per year