1 day ago
Base Salary
$163k - $288k/yr
Responsibilities
- Lead technical design decisions for the AI model-serving platform, focusing on performance, reliability, and scalability.
- Design, implement, maintain, and scale distributed systems for moving ML models into production.
- Write design documents, build cross-team consensus, and evaluate new technologies.
- Improve and scale continuous integration software pipelines.
- Respond to production alerts, debug issues, and maintain platform health and reliability.
- Review pull requests for consistency, performance, readability, and security.
- Collaborate with software engineers, machine learning engineers, and data scientists, while mentoring engineers and documenting knowledge.
Requirements
- 6+ years of related software development experience focused on large-scale distributed systems.
- Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
- Deep hands-on experience deploying and scaling Kubernetes workloads with GPU resource management.
- Experience optimizing GPU utilization for hosting and tuning open-weight LLMs using inference engines such as vLLM or SGLang.
- Familiarity with GPU memory constraints, LoRA-tuned model serving, and autoscaling based on hardware metrics.
- Deep experience designing, building, and scaling production-grade distributed systems and applying software development lifecycle practices.
- Deep proficiency in Python and experience building production systems with Python-based frameworks.
- Familiarity with serving, scaling, and monitoring both LLMs and traditional ML models in production.
- Ability to design monitoring strategies for system health, performance, and cost.
- Strong written and verbal communication, design-documentation, consensus-building, mentoring, and inclusive collaboration skills.
Benefits
- Potential eligibility for the Workday Bonus Plan or role-specific 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 flexibility.
- Application deadline is October 30, 2026.
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.