Senior Staff Software Engineer, Machine Learning - Slack

Salesforce - Atlanta, GA

Full-time - Senior

Atlanta, GA

Publishing Industries

About the position

The Senior Machine Learning Engineer at Slack will be responsible for crafting and implementing machine learning and generative AI powered features that enhance the user experience. This role involves collaboration with cross-functional teams to conceptualize new features, lead significant projects, and ensure the long-term health of systems. The engineer will also mentor other engineers and improve engineering standards and processes.

Responsibilities

• Brainstorm with Product Managers, Designers, and Frontend Engineers to conceptualize and build new features for a large user base.
• Produce high-quality results by leading or contributing heavily to large multi-functional projects that significantly impact the business.
• Actively own features or systems and define their long-term health while improving the health of surrounding systems.
• Assist the support and operations teams in triaging and resolving production issues.
• Mentor other engineers and conduct deep code reviews.
• Improve engineering standards, tooling, and processes.

Requirements

• 10+ years experience with machine learning and software engineering.
• Experience putting machine learning models, generative AI, or other data-derived artifacts into production at scale, especially for text-based applications.
• Experience working on generative AI apps with Large Language Models and improving quality through various methods.
• Proficiency in functional or imperative programming languages such as PHP, Python, Ruby, Go, C, Scala, or Java.
• Experience with ML frameworks like PyTorch, TensorFlow, Keras, XGBoost, or Scikit-learn.
• Experience building batch data processing pipelines with tools like Apache Spark, SQL, Hadoop, EMR, Map Reduce, Airflow, Dagster, or Luigi.
• Analytical and data-driven mindset with the ability to measure success with complex ML/AI products.
• Experience leading technical architecture discussions and driving technical decisions within the team.
• Ability to write understandable, testable code with a focus on maintainability.
• Strong communication skills to explain technical concepts to non-technical stakeholders.
• Strong computer science fundamentals: data structures, algorithms, programming languages, distributed systems, and information retrieval.
• Bachelor's degree in Computer Science, Engineering, Statistics, Mathematics, or a related field, or equivalent training, fellowship, or work experience.

Nice-to-haves

• Deployed production RAG pipelines.
• Experience with LLM evaluation and monitoring at scale.
• Experience in A/B testing and experimentation.