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 focused on responsible AI development. This role combines technical expertise with ethical considerations in AI development. Working closely with Einstein product teams, AI Frontier, and Salesforce AI Research teams, you'll ensure AI systems align with ethical guidelines and policies. The position involves building and assessing machine learning models, developing tools for fair and transparent AI, and collaborating across multiple teams.
The ideal candidate will lead technical initiatives in responsible AI development, working on both generative and predictive models. You'll be responsible for measuring and mitigating bias in data and models, creating testing datasets, and developing quantitative metrics for structured data analysis. The role requires strong technical skills in Python, SQL, and machine learning frameworks, combined with an understanding of fairness in AI systems.
As a senior member of the team, you'll contribute to building tools and libraries for testing and evaluating content safety and algorithmic bias. The position offers the opportunity to work with industry leaders and shape the future of responsible AI development. You'll need strong communication skills to present ideas to diverse teams and the ability to work effectively in a fast-paced environment.
The role combines technical excellence with ethical considerations, making it perfect for someone passionate about using technology as a force for social good. You'll be at the forefront of ensuring AI systems are developed responsibly, working with cutting-edge technology while considering its societal impact. This position offers the chance to influence how AI is implemented across Salesforce's products while collaborating with some of the best minds in the field.
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, both generative and predictive
- Drive engineering investments in responsible AI to improve model fairness and safety
- Create notebooks using SQL or Python for advanced analytics
- Develop quantitative metrics for structured datasets
- Monitor and analyze logs data for harms/threats and insights
- 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
- 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
- Knowledge of fairness evaluation in AI
- Experience working across teams of engineers, data scientists, and researchers
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