Software Engineer, Machine Learning (Multiple Levels) - Slack

About the Role

Key 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 a large 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 support and operations teams in triaging and resolving production issues.
• Mentor other engineers and deeply review code.
• Improve engineering standards, tooling, and processes.

Requirements

• 7+ years of applicable engineering experience.
• Experience with functional or imperative programming languages such as 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, MapReduce, Airflow, Dagster, or Luigi.
• Worked on generative AI applications with Large Language Models and possibly fine-tuned them.
• An analytical and data-driven mindset with the ability to measure success in ML/AI products.
• Experience deploying machine learning models or data-derived artifacts at scale.
• Experience leading technical architecture discussions and driving technical decisions.
• Ability to write understandable, testable, and maintainable code.
• Strong communication skills capable of explaining complex technical concepts to diverse teams.
• Strong computer science fundamentals including data structures, algorithms, distributed systems, and information retrieval.

Nice to Have

• 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.

Qualifications

• Educational background is not explicitly specified but requires extensive engineering experience and technical expertise.

Benefits & Perks

• Time off programs
• Medical, dental, and vision insurance
• Mental health support
• Paid parental leave
• Life and disability insurance
• 401(k)
• Employee stock purchasing program
• Additional details available at https://www.salesforcebenefits.com