Machine Learning Engineer

About 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 users. We seek candidates with experience or interest in search / conversational agents, and engineers who can drive impact with machine learning across the organization.

What you will be doing

• 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.

What you should have

• Experience with functional or imperative programming languages: PHP, Python, Ruby, Go, C, Scala or Java.
• Experience with common ML frameworks such as PyTorch, TensorFlow, Keras, XGBoost or Scikit‑learn.
• Experience building batch data processing pipelines with tools such as Apache Spark, Hadoop, EMR, MapReduce, Airflow, Dagster or Luigi.
• Experience building generative AI applications with large language models (LLMs) and possibly fine‑tuning them.
• Analytical and data‑driven mindset, and the ability to measure success with complex ML/AI products.
• Experience deploying machine learning models or other data‑derived artifacts at scale.
• Experience leading technical architecture discussions and driving technical decisions within the team.
• Ability to write understandable, testable code with an eye toward maintainability.
• Strong communication skills and the ability to explain complex technical concepts to designers, support, and other specialists.
• Strong computer science fundamentals: data structures, algorithms, programming languages, distributed systems, and information retrieval.
• A bachelor’s degree in Computer Science, Engineering, Statistics, Mathematics or a related field, or equivalent training, fellowship, or work experience.

Nice to have

• Experience building and optimizing Retrieval‑Augmented Generation (RAG) pipelines.
• Expertise in conversational agents.
• Expertise in retrieval systems and search algorithms.
• Familiarity with vector databases and embeddings.
• Broad experience across NLP, ML, and generative AI capabilities.

Accommodations

If you need a reasonable accommodation during the application or recruiting process, please submit a request via an Accommodations Request Form.

Posting Statement

Salesforce is an equal‑opportunity employer and maintains a policy of non‑discrimination with all employees and applicants for employment. All employees and candidates are assessed based on merit, competence and qualifications, without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law.

Compensation and Benefits

For British Columbia‑based roles, the base salary hiring range for this position is CAD $160,000 to $179,200. For Ontario‑based roles, the base salary hiring range is CAD $160,000 to $179,200 annually. The range represents base salary only and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.