Software Engineer, Machine Learning (SWE II & SWE I)

Slack•Indianapolis, IN

23h

About The Position

Salesforce, the #1 AI CRM, is seeking a Machine Learning Engineer for Slack. This role involves crafting and implementing features, services, API methods, and models to leverage data, making Slack a robust, safe, and valuable product. The team focuses on agentic systems (like Slackbot), search, and recommendation, driving innovation in conversational intelligence. Slack serves over 10 million daily active users, processing a million messages per minute at peak and over a billion active minutes daily. Machine learning engineers engage with various technical aspects, including building data pipelines, training recommendation models, fine-tuning LLMs, implementing application features, and analyzing experiment data. This is a practical, impact-driven team, not a research team, aiming to deliver business value through machine learning and data, ranging from simple logistic regressions to sophisticated, novel solutions tailored to Slack's unique challenges. The ideal candidate is driven by business impact, product excellence, and delivering robust, reliable ML services.

Requirements

Experience with functional or imperative programming languages: PHP, Python, Ruby, Go, C, Scala or Java.
Built with common ML frameworks like PyTorch, Tensorflow, Keras, XGBoost, or Scikit-learn
Fine tuned LLMs or BERT models.
Experience building batch data processing pipelines with tools like Apache Spark, Hadoop, EMR, Map Reduce, Airflow, Dagster, or Luigi.
An analytical and data driven mindset, and know how to measure success with complicated ML/AI products.
Put machine learning models or other data-derived artifacts into production at scale.
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.

Nice To Haves

Expertise in conversational agentic systems.
Expertise in retrieval systems and search algorithms.
Familiarity with vector databases and embeddings.
Knowledge of using multiple data types in RAG solutions including structured, unstructured, and knowledge graphs.
Broad experience across NLP, ML, and Generative AI capabilities.

Responsibilities

Leveraging machine learning and artificial intelligence subject matter expertise to drive improvements in the Slackbot experience.
Develop ML models supporting ranking, retrieval, and generative AI use-cases.
Brainstorm with Product Managers, Designers and Frontend Engineers to conceptualize and build new features for our large (and growing!) user base.
Produce high-quality results by leading or contributing heavily to large multi-functional projects that have a significant impact on the business.
Actively own features or systems and define their long-term health, while also improving the health of surrounding systems.
Support in the development of sustainable data collection pipelines and management of ML features.
Assist our skilled support team and operations team in triaging and resolving production issues.
Mentor other engineers and deeply review code.
Improve engineering standards, tooling, and processes.