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 core 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: 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 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.

Requirements

• 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.

Qualifications

• Nice to have: Expertise with recommendation systems or search.
• Familiarity with model optimization for inference (quantization, pruning, speculative decoding, compilation via TorchScript/TensorRT/ONNX).
• Experience with retrieval-augmented generation and hybrid retrieval/generation systems.
• Broad experience across NLP, ML, and Generative AI capabilities.
• Knowledge of using multiple data types in RAG solutions including structured, unstructured, and knowledge graphs.
• Broad experience across NLP, ML, and Generative AI capabilities.

Skills

• Deep training and productionization expertise.
• Hands-on experience with model training and finetuning.
• Experience with common deep learning frameworks.
• Experience with functional or imperative programming languages.
• Data-driven mindset and ability to measure success with ML/AI products.
• Technical leadership and mentorship skills.
• Communication and collaboration skills.

Benefits

At Salesforce, we offer a comprehensive benefits package including:

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

Pay

$197,300 - $313,700 annually

Schedule

Full-time