Posted:
7/16/2024, 5:00:00 PM
Location(s):
Melbourne, Victoria, Australia ⋅ Perth, Western Australia, Australia ⋅ Western Australia, Australia ⋅ Sydney, New South Wales, Australia ⋅ Queensland, Australia ⋅ New South Wales, Australia ⋅ Brisbane City, Queensland, Australia ⋅ Victoria, Australia
Experience Level(s):
Mid Level ⋅ Senior
Field(s):
AI & Machine Learning ⋅ Data & Analytics
To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.
Job Category
DataJob Details
About Salesforce
We’re Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good – you’ve come to the right place.
Team Overview
Salesforce's Office of Ethical and Humane Use is looking for an experienced ML data scientist with a focus on responsible AI. Working with the Einstein product and engineering teams, AI Frontier, and Salesforce AI Research teams, they support the development of foundation and predictive models by ensuring they are built and deployed in alignment with OEHU’s guidelines and policies.
The Role
The ideal candidate is well-versed in assessing a variety of machine learning techniques to provide actionable insights on how to bring them into production. They are enthusiastic about providing technical and scientific leadership to teams of scientists and engineers. They build tools to ensure fair, accountable, transparent, and explainable AI. This individual will support our culture of being proactive, thoughtful, and knowledgeable about Salesforce’s AI products.
Job Responsibilities:
Partner with the Salesforce AI Research Science team, as well as distributed Data Science and Engineering teams, to measure and remediate potential bias in data and models.
Build datasets for testing models, both generative and predictive, in collaboration with partner teams
Participate in technical discussions, and drive engineering investments in responsible AI to improve model fairness and safety prior to launch
Develop quantitative metrics to help surface insights from structured datasets
Plan and conduct end-to-end experiments and analyses, from gathering requirements through processing and modeling the data, to identifying emerging risks
Assist in data curation to develop safety detectors
Validate any synthetic data generation, crowdsource, or contractor jobs for labeling or data creation
Participate in labeling test data in partnership with OEHU and partner teams
Collaborate with industry leaders in similar positions in peer organizations on ways to improve the state of responsible AI development
Job Requirements/Required Skills
Practical experience in machine learning
MS in a quantitative discipline with 8+ years of experience
Fluent in building/prototyping machine learning models and algorithms and wrangling large datasets.
Knowledgeable about standard machine learning approaches (Regression, Cross-Validation, Boosting, Matrix-Factorization, Decision Trees, Clustering, CNNs, RNNs, Transformers, GANs).
Proficient in using Python and common machine learning frameworks (e.g., TensorFlow, Pandas, PyTorch, SciPy, scikit-learn, JAX) to implement models and algorithms.
Proficient in SQL, shell scripting, and Unix/Linux command-line tools.
Grasp of the evolving understanding of fairness and ability to meet both state-of-the-art and global standards for fairness evaluation, particularly in generative AI
Experience working across teams of engineers, data scientists, and researchers.
Strong communication skills. Comfortable presenting ideas to diverse teams and individuals in multiple formats, from slide decks to informal chats.
Earns trust in relationships both internally and externally, and at all levels of the organization. Challenges the status quo to improve the productivity, effectiveness, and culture of a team - without burning bridges.
Ability to creatively prioritize, stage, and sequence solutions to challenging/complex problems.
Desired Skills
Demonstrated experience with bringing data science solutions from problem identification to production
Experience with designing and building micro-services, familiar with Kubernetes/containerization/RESTful API/gRPC, etc.
Experience building and training various deep learning algorithms from scratch
Strong experience leading multi-disciplinary teams driving significant business results
Passion for the idea that technology can be a force for social good and for ethics and fairness.
Ability to stay abreast of the latest findings in the field, new technologies, and best practices
Knowledge of enterprise SaaS space
Works well under pressure, and is comfortable working in a fast-paced, ever-changing environment.
Accommodations
If you require assistance due to a disability applying for open positions please submit a request via this Accommodations Request Form.
Posting Statement
At Salesforce we believe that the business of business is to improve the state of our world. Each of us has a responsibility to drive Equality in our communities and workplaces. We are committed to creating a workforce that reflects society through inclusive programs and initiatives such as equal pay, employee resource groups, inclusive benefits, and more. Learn more about Equality at www.equality.com and explore our company benefits at www.salesforcebenefits.com.
Salesforce is an Equal Employment Opportunity and Affirmative Action Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status. Salesforce does not accept unsolicited headhunter and agency resumes. Salesforce will not pay any third-party agency or company that does not have a signed agreement with Salesforce.
Salesforce welcomes all.
Website: https://www.salesforce.com/
Headquarter Location: San Francisco, California, United States
Employee Count: 10001+
Year Founded: 1999
IPO Status: Public
Last Funding Type: Post-IPO Equity
Industries: Apps ⋅ Cloud Computing ⋅ CRM ⋅ Enterprise Software ⋅ Information Technology ⋅ iOS ⋅ Mobile Apps ⋅ SaaS ⋅ Sales Enablement ⋅ Software