1 day ago
Base Salary
$191k - $342k/yr
Responsibilities
- Design and implement agentic AI capabilities, including tool calling, multi-agent workflows, long-range planning, reasoning frameworks, and human-in-the-loop integrations.
- Build secure, high-throughput ML services, event-driven data pipelines, multi-tenant runtimes, and low-latency inference infrastructure.
- Establish MLOps standards covering CI/CD automation, observability, evaluation frameworks, model monitoring, privacy, anonymization, and production resilience.
- Lead model building, fine-tuning, deployment, retraining, drift management, and latency management for domain-specific foundation models.
- Develop high-throughput streaming, real-time feature extraction, distributed storage, vector database, and data-isolation solutions for large-scale ML pipelines.
- Partner with software engineering, product management, data engineering, SRE, and legal/compliance stakeholders on scalable designs and data-governance strategies.
- Technically lead cross-functional pods, mentor engineers, drive sprint planning, and communicate technical and governance decisions to executives.
Requirements
- 12+ years of experience in ML development and R&D leadership, including 8+ years with advanced ML methodologies, distributed frameworks, and cloud-based 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 for enterprise applications.
- Expertise in Kafka, Spark or Flink, ClickHouse, and Iceberg for streaming, feature extraction, and distributed data processing.
- Deep knowledge of deep learning, LLM orchestration, RAG, agentic systems, ML algorithms, Model-Based Design, MCP integrations, and tool-use frameworks.
- Experience with exploratory data analysis, high-dimensional embeddings, vector databases, multi-tenant workflows, and data isolation.
- Mastery of Python and ML technologies including PyTorch, TensorFlow, LangChain, LangSmith, LlamaIndex, NumPy, Pandas, and Scikit-learn.
- Strong experience deploying production systems with PostgreSQL, Redis, Kafka, Kubernetes, Docker, and AWS, GCP, or Azure.
- Bachelor’s degree in computer science, data science, statistics, mathematics, engineering, or a related field, or equivalent experience; a master’s degree or PhD is strongly preferred.
- Demonstrated technical leadership, cross-functional collaboration, mentoring, sprint planning, and executive communication skills.
Benefits
- Annualized base salary ranges are $228,000-$342,000 for the primary Pleasanton, California location and $190,600-$342,000 for additional U.S. locations.
- May be eligible for the Workday Bonus Plan or role-specific commission/bonus and annual refresh stock grants.
- Flexible work arrangement requiring at least 50% of each quarter in the office or in the field, with remote home-office options and opportunities to gather in company offices.
- Workday offers comprehensive benefits, reasonable accommodations, equal employment opportunity, and fair-chance consideration.
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.