Staff ML Engineer, Fine Tuning - Slack

About the role

Slack is seeking a Staff Machine Learning Engineer to join our ML team. This role involves designing, training, and deploying NLP models that power key product experiences.

Responsibilities

• Design and execute finetuning strategies for large language models and other 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 for our growing user base.
• Lead large multi-functional projects that significantly impact the business.
• Mentor other engineers and deeply review code.
• Improve engineering standards, tooling, and processes.

Requirements

• 5+ years of hands-on experience training and fine-tuning deep learning models in NLP (or a closely related domain).
• Experience with common deep learning frameworks like PyTorch, TensorFlow, JAX, etc.
• An analytical and data-driven mindset, with the ability to measure success with complicated ML/AI products.
• Experience with functional or imperative programming languages.
• Strong communication skills to explain complex technical concepts to designers, support, and other specialists.

Qualifications

• Track record of shipping fine-tuned models to production that serve real users at scale.
• 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.

Skills

• Deep training and productionization expertise.
• Broad experience across NLP, ML, and Generative AI capabilities.
• Experience with recommendation systems or search.
• Experience with model optimization for inference (quantization, pruning, speculative decoding, compilation via TorchScript/TensorRT/ONNX).
• Experience with retrieval-augmented generation and hybrid retrieval/generation systems.

Benefits

At Salesforce, we offer a comprehensive benefits package including:

• Time off programs
• Medical, dental, vision, and mental health support
• Paid parental leave
• Life and disability insurance
• 401(k)
• Employee stock purchasing program

For more details, visit Salesforce Benefits.

The typical base salary range for this position is $197,300 - $313,700 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range is $237,700 - $344,700 annually.