Software Engineer, Machine Learning (SWE II & SWE I)

TL;DR

Software Engineer, Machine Learning (SWE II & SWE I) (Machine Learning/Generative AI): Building production machine learning features, services, data pipelines, and models for hirify.globalbot, search, recommendations, and conversational intelligence with an accent on ranking, retrieval, LLM fine-tuning, and reliable large-scale systems. Focus on developing practical ML solutions, deploying models into production, measuring complex AI products, and improving system health across high-traffic services.

Location: San Francisco, California, United States; onsite role

Salary: $128,500–$260,100 annually; in select San Francisco and New York metropolitan areas, $141,200–$285,800 annually.

Company

hirify.global is a large-scale workplace collaboration product within Salesforce, serving more than 10 million daily active users and supporting high-volume messaging and AI-powered experiences.

What you will do

• Develop machine learning models for ranking, retrieval, recommendations, and generative AI use cases.
• Build features and services that improve the hirify.globalbot and conversational intelligence experience.
• Design sustainable data collection pipelines and manage machine learning features and artifacts.
• Lead or make substantial contributions to cross-functional projects with Product Managers, Designers, and Frontend Engineers.
• Own the long-term health of features and systems, resolve production issues, and improve engineering standards and tooling.
• Mentor engineers, review code, and contribute to technical architecture decisions.

Requirements

• Experience with PHP, Python, Ruby, Go, C, Scala, or Java.
• Experience using ML frameworks such as PyTorch, TensorFlow, Keras, XGBoost, or Scikit-learn.
• Experience fine-tuning LLMs or BERT models and deploying machine learning models into production at scale.
• Experience building batch data-processing pipelines with tools such as Apache Spark, Hadoop, EMR, MapReduce, Airflow, Dagster, or Luigi.
• Ability to measure the success of complex ML and AI products, lead architecture discussions, and write maintainable, testable code.
• Strong communication skills for explaining technical concepts to technical and non-technical specialists.

Nice to have

• Expertise in conversational agentic systems, retrieval systems, or search algorithms.
• Familiarity with vector databases, embeddings, RAG solutions, and knowledge graphs.
• Broad experience across NLP, machine learning, and generative AI.

Culture & Benefits

• Work on AI and machine learning products used at significant global scale.
• Benefits include medical, dental, vision, mental health support, paid parental leave, life and disability insurance, and 401(k).
• Additional benefits may include equity, incentive compensation, paid time off, and an employee stock purchasing program.
• Inclusive workplace with reasonable accommodations available throughout the recruiting process.