Responsible ML Data Science Engineer
Description For Responsible ML Data Science Engineer
Salesforce's Office of Ethical and Humane Use is seeking an experienced ML data scientist focusing on responsible AI. This role involves collaborating with Einstein product, engineering teams, AI Frontier, and Salesforce AI Research teams to ensure AI models align with ethical guidelines. The position combines technical expertise in machine learning with a focus on fairness, accountability, and transparency in AI systems. You'll work on building and evaluating AI models, developing tools for bias detection, and ensuring responsible AI practices. The role requires both technical proficiency in ML/AI and strong collaborative skills to work across various teams. This is an opportunity to impact how AI is developed and deployed ethically at a major enterprise software company, working on cutting-edge technology while ensuring it serves as a positive force for society. The position offers competitive compensation and the chance to work with industry leaders in responsible AI development.
Responsibilities For Responsible ML Data Science Engineer
- Partner with AI Research Science team to measure and remediate potential bias in data and models
- Build datasets for testing models
- Participate in technical discussions and drive engineering investments in responsible AI
- Create notebooks using SQL or Python for advanced analytics
- Develop quantitative metrics for structured datasets
- Monitor and analyze logs data for harms/threats
- Validate synthetic data generation and labeling
- Contribute to libraries and tools for testing and evaluation
- Extract logs and data from various parts of the tech stack for analysis
Requirements For Responsible ML Data Science Engineer
- MS in a quantitative discipline with 8+ years of experience
- Practical experience in machine learning
- Fluent in building/prototyping machine learning models and algorithms
- Knowledge of standard machine learning approaches
- Proficient in Python and common machine learning frameworks
- Proficient in SQL, shell scripting, and Unix/Linux command-line tools
- Experience with designing and building micro-services
- Strong communication skills
- Understanding of fairness evaluation in AI
- Experience working across teams of engineers, data scientists, and researchers
