(Senior) Machine Learning Software Engineer, Salesforce

• We are looking for engineers who are driven by driving impact for our business, building great products for our customers, and delivering robust, reliable services with machine learning
• 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
• Expertise in retrieval systems and search algorithms
• Knowledge of using multiple data types in RAG solutions including structured, unstructured, and knowledge graphs

Desirable

• Slack is looking for a Machine Learning Engineer to craft and implement features, services, API methods, and models to leverage our data to make Slack a fabulous, robust, safe, and valuable product for our users
• We work on applications across agentic systems (Slackbot), search, recommendation, and more, but ultimately are looking for engineers excited to drive impact at the forefront of conversational intelligence
• At Slack, that impact can be huge:
• We have over 10 million daily active users relying on our product
• At peak usage, a million messages a minute pass through Slack
• During the week, our users spend over a billion minutes a day active in our product
• Machine learning engineers at Slack touch a great variety of parts of our technical stack
• At different points, you might find yourself building data pipelines, training recommendation models, fine tuning LLMs, implementing features in our application, or analyzing experiment data
• We don’t expect everyone to be an expert in everything, but we are looking for candidates with experience in Machine Learning, a strength in at least a couple of these, and who are excited to learn the rest
• This is a practical machine learning team, not a research team
• Our goal is to deliver business value with machine learning and data in whatever form that takes. Sometimes that means bootstrapping something simple like a logistic regression and moving on
• Other times that means developing sophisticated, finely tuned models and novel solutions to Slack’s unique problem space
• 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

• End Date: March 19, 2026