1 day ago
Dublin, IrelandStaff+
Responsibilities
- Own the technical vision, architecture, and roadmap for Workday’s anonymization capability.
- Lead applied privacy research involving differential privacy, group anonymization, synthetic data generation, and emerging privacy-preserving techniques.
- Build and evaluate anonymization models, calibrate privacy parameters against utility, and conduct adversarial evaluations of privacy guarantees.
- Lead the anonymization engineering group through technical planning, design reviews, code reviews, hiring, and mentoring.
- Define architectural standards and interfaces for teams consuming anonymized data.
- Partner with Product Legal, compliance, product, executive stakeholders, and external research partners on privacy, data governance, and technical strategy.
- Represent Workday’s anonymization work in external research, benchmarking, standards, and industry engagements.
Requirements
- 10+ years of hands-on experience in Machine Learning Engineering, Data Science, or applied research, including leading initiatives from research through enterprise production deployment.
- Demonstrable expertise in privacy-preserving machine learning, differential privacy, group anonymization, or synthetic data generation.
- Expert-level Python experience and proficiency with modern machine learning frameworks such as PyTorch or TensorFlow.
- Experience architecting and operating large-scale data-processing pipelines using Spark or equivalent distributed frameworks.
- Experience driving engineers through ambiguous technical problems, setting cross-team architecture standards, and mentoring mid-level and senior engineers.
- Bachelor’s degree in Computer Science, Physics, Mathematics, or a related quantitative field, or equivalent practical experience.
- Preferred experience with classification, Named-Entity Recognition, transformer architectures, Hugging Face, LLM fine-tuning, and GPU inference optimization.
- Preferred Master’s or Ph.D. in Computer Science, Machine Learning, Statistics, or a related quantitative discipline.
- Preferred experience deploying, scaling, and maintaining machine learning systems on AWS or an equivalent cloud platform.
- Preferred experience with agent execution, agent orchestration, or LLM evaluation frameworks such as LangGraph and LangSmith.
- Preferred understanding of Responsible AI, bias and fairness evaluation, GDPR, and technical collaboration with legal and compliance teams.
- Preferred experience directing external research partners, consultancies, or academic collaborators.
- Publications, patents, open-source contributions, or conference work in privacy-preserving machine learning are valued.
Benefits
- Flexible work arrangement combining remote and in-person work, with at least 50% of each quarter spent in the office or in the field.
- Role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus and annual refresh stock grants.
- Workday provides reasonable accommodations and is an equal opportunity employer.
Tech Stack
Categories
About Workday
Workday builds cloud-based enterprise applications for human capital management and financial management, including payroll, time tracking, expenses, planning, and procurement, sold on a subscription basis with professional services. Founded in 2005 and headquartered in Pleasanton, California, it is a public company traded on NASDAQ as WDAY. Organizations worldwide use Workday to unify HR and finance data, automate processes, and apply AI to workforce and financial operations.