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Workday

Builds software to manage HR and finances

Principal ML Engineer - Admin Central

Applied Machine LearningUpdated on Nov 5
Full-timePleasanton, CA, USA

About the Job

Requirements

  • At least 12 years of experience in machine learning development and research and development leadership, including at least 8 years with advanced machine learning methodologies, distributed frameworks, and cloud-based platforms designing complex, scalable, production-grade machine learning systems.
  • At least 6 years building and hosting scalable machine learning services, microservices, and high-throughput data pipelines in production using Java, Go, Scala, or Python.
  • At least 4 years working with large language models, generative AI, retrieval-augmented generation pipelines, and autonomous agent frameworks for real-world enterprise applications.
  • Expertise in high-throughput streaming with Kafka, real-time feature extraction with Spark or Flink, and distributed columnar storage with ClickHouse or Iceberg for large-scale machine learning pipelines.
  • Deep knowledge of deep learning, large language model orchestration, retrieval-augmented generation, and agentic systems, including machine learning algorithms and Model-Based Design, MCP integrations, and tool-use frameworks for multi-agent coordination, intent classification, and workflow optimization.
  • Ability to lead exploratory data analysis on multi-tenant agentic workflows and shape data strategy, with expertise in high-dimensional embeddings, vector database management, and data isolation.
  • Ability to lead model building, fine-tuning, and deployment of domain-specific foundation models, including Kubernetes or Docker deployment, automated continuous integration and continuous deployment retraining, and management of model drift and latency at scale.
  • Mastery of Python and the machine learning ecosystem, including PyTorch, TensorFlow, LangChain, LangSmith, LlamaIndex, NumPy, Pandas, and Scikit-learn.
  • Strong experience deploying production systems on PostgreSQL, Redis, Kafka, and cloud infrastructure such as AWS, Google Cloud Platform, or Microsoft Azure.
  • Strong collaboration and mentoring skills, with the ability to technically lead cross-functional pods, drive sprint planning, and translate technical and governance decisions for executives.
  • Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field, or equivalent experience.

Responsibilities

  • Lead the architecture and implementation of next-generation AI platforms and autonomous agent frameworks.
  • Design, implement, and maintain agentic capabilities, including tool calling, multi-agent workflows, long-range planning, reasoning frameworks, and human-in-the-loop integrations.
  • Build secure, high-throughput REST services and event-driven data pipelines using Python, AWS, Kubernetes, and cloud-native technologies.
  • Architect multi-tenant runtimes that deliver fast, low-latency inference to millions of global users.
  • Establish end-to-end MLOps standards, including continuous integration and continuous delivery automation, observability, evaluation frameworks, model monitoring, and privacy and anonymization guardrails.
  • Partner with software engineers, Product Managers, Data Engineering, Site Reliability Engineering, and Legal and Compliance stakeholders to turn ambiguous business needs into scalable technical designs and long-term data-governance strategies.
  • Design machine learning infrastructure, multi-agent orchestration layers, and high-availability usage pipelines powering enterprise decision-making, usage tracking, automatic tenant maintenance, and billing integrity across international regions.

Desired Qualifications

  • A master's degree or PhD is strongly preferred.

About the Company

Workday

Builds software to manage HR and finances

Workday builds cloud software that organizations use to manage employees, finances, and business plans. Its Human Capital Management and Financial Management applications handle processes such as hiring, payroll, expenses, accounting, and reporting, while Adaptive Planning helps teams build budgets and forecasts. Users work in connected applications with shared data and permissions, and Workday also sells AI tools that search information and carry out HR and finance tasks. Customers pay for subscriptions, with additional revenue from implementation, training, and other professional services. Workday was founded in 2005 and is headquartered in Pleasanton, California.

Company size
10,001+
Company stage
IPO
Headquarters
Pleasanton, CA
Founded
2005

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