2 days ago
Base Salary
$191k - $342k/yr
Responsibilities
- Design and maintain agentic AI capabilities including tool calling, multi-agent workflows, planning, reasoning frameworks, and human-in-the-loop integrations.
- Build scalable ML infrastructure, secure high-throughput services, multi-tenant runtimes, and event-driven data pipelines using Python, AWS, Kubernetes, and cloud-native technologies.
- Establish MLOps practices covering CI/CD automation, observability, evaluation, model monitoring, privacy, anonymization, explainability, and production resilience.
- Lead model building, fine-tuning, deployment, retraining, and drift and latency management for domain-specific foundation models.
- Partner with software engineering, product management, data engineering, SRE, legal, and compliance stakeholders on technical and data-governance strategy.
- Technically lead cross-functional pods, mentor engineers, drive sprint planning, and translate technical and governance decisions for executives.
Requirements
- 12+ years of ML development and R&D leadership experience, including 8+ years with advanced ML methodologies, distributed frameworks, and cloud platforms.
- 6+ years building and hosting scalable ML services, microservices, and high-throughput production data pipelines using Java, Go, Scala, or Python.
- 4+ years working with LLMs, generative AI, RAG pipelines, and autonomous agent frameworks in enterprise applications.
- Expertise with Kafka, Spark or Flink, ClickHouse or Iceberg, high-dimensional embeddings, vector databases, data isolation, and large-scale ML pipelines.
- Deep knowledge of deep learning, LLM orchestration, RAG, agentic systems, Model-Based Design, MCP integrations, tool-use frameworks, and workflow optimization.
- Mastery of Python and the ML ecosystem, including PyTorch, TensorFlow, LangChain, LangSmith, LlamaIndex, NumPy, Pandas, and Scikit-learn.
- Strong experience deploying production systems using PostgreSQL, Redis, Kafka, and AWS, GCP, or Azure.
- Bachelor’s degree in computer science, data science, statistics, mathematics, engineering, or a related field, or equivalent experience; master’s degree or PhD strongly preferred.
- Exceptional collaboration, mentoring, technical leadership, and executive communication skills.
Benefits
- Annualized base salary ranges from $228,000 to $342,000 for the primary Pleasanton location and from $190,600 to $342,000 for additional US locations, with possible bonus and annual refresh stock grants.
- Flex Work combines in-person and remote work, with at least 50% of each quarter spent in the office or in the field with customers, prospects, or partners.
- Workday provides equal employment opportunity, reasonable accommodations, and consideration under applicable Fair Chance laws.
Tech Stack
Apache FlinkApache KafkaApache SparkAWSAzureClickHouseDockerGoGoogle Cloud PlatformJavaKubernetesNumPyPandasPostgreSQLPythonPyTorchRedisScalascikit-learnTensorFlow
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.