Software Engineer (Machine Learning - Slack)

• 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 search, agentic systems, recommendation, and security, but ultimately are looking for engineers who can help drive impact with machine learning across the organization
• 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
• 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
• 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

Benefits

• Medical Care
• Life Insurance
• Retirement Savings
• Employee Assistance Programs
• With 9 standard holidays and four floating holidays, you get a total 13 paid days off each year- - Built with common ML frameworks like pytorch, Tensorflow, Keras, XGBoost, or Scikit-learn
• • Led technical architecture discussions and helped drive technical decisions within the team
• • Put machine learning models or other data-derived artifacts into production at scale
• • Strong computer science fundamentals: data structures, algorithms, programming languages, distributed systems, and information retrieval
• • Experience with functional or imperative programming languages: PHP, Python, Ruby, Go, C, Scala or Java
• • Fine tuned LLMs or BERT models
• • The ability to write understandable, testable code with an eye towards maintainability
• • 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
• • Strong communication skills and you are capable of explaining complex technical concepts to designers, support, and other specialists
• • A bachelor’s degree in Computer Science, Engineering, Statistics, Mathematics or a related field, or you have equivalent training, fellowship, or work experience
• • Expertise in conversational agentic systems
• • Expertise in retrieval systems and search algorithms
• • Broad experience across NLP, ML, and Generative AI capabilities
• • Knowledge of using multiple data types in RAG solutions including structured, unstructured, and knowledge graphs
• • Familiarity with vector databases and embeddings