Software Engineer II, Machine Learning (Search) - Slack

Salesforce•Vancouver, BC

About The Position

Salesforce is seeking a Machine Learning Engineer for Slack to develop and implement features, services, API methods, and models that leverage data to enhance Slack's functionality, robustness, safety, and value for users. The role involves driving impact with machine learning across the organization, with a focus on search and conversational agents. Machine learning engineers at Slack work on various aspects of the technical stack, including data pipelines, training search ranking models, fine-tuning LLMs, implementing application features, and analyzing experiment data. This is a practical machine learning team focused on delivering business value through data and machine learning, ranging from simple models like logistic regression to sophisticated, finely tuned models and novel solutions for Slack's unique challenges. The ideal candidate is driven by business impact, customer-focused product building, 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
Experience building batch data processing pipelines with tools like Apache Spark, Hadoop, EMR, Map Reduce, Airflow, Dagster, or Luigi.
Worked on generative AI apps with Large Language Models and possibly fine tuned them
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.
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 you have equivalent training, fellowship, or work experience.

Nice To Haves

Experience building and optimizing 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.

Responsibilities

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.