Workday
Senior/Principal Machine Learning Engineer
Workday, Pleasanton, California, United States, 94566
Senior/Principal Machine Learning Engineer
Join Workday as a Senior/Principal Machine Learning Engineer, a key role in advancing AI‑driven solutions that shape the future of work. About the Team
Agent Factory is a small, senior, cross‑functional AI team focused on building production‑grade intelligent agents used by millions daily. The team owns end‑to‑end problem ownership and collaborates closely across product, engineering, and data science. About the Role
As a Senior/Principal Machine Learning Engineer you will design and build the core ML systems behind Workday’s next generation of AI agents. You’ll own model development, agent logic, orchestration layers, and the entire ML lifecycle—from data strategy and model design to deployment, monitoring, and continuous improvement. You’ll implement frameworks for LLM‑powered agents, including RAG pipelines, workflow orchestration, evaluation, and feedback loops, ensuring scalability, observability, and enterprise readiness. P5, Principal Machine Learning Engineer - Basic Qualifications
10+ years of experience building applied machine learning products at scale, including research, design, implementation, production, and evaluation. 4+ years of experience with deep learning frameworks such as Pytorch or TensorFlow. 6+ years of experience building production‑scale services that host ML models. 3+ years of experience working with large language models (LLMs), text generation models, or graph neural networks for real‑world use cases. 6+ years of experience with cloud platforms (AWS, GCP, etc.). Proven track record of leading, mentoring, and managing ML engineering teams, overseeing the development lifecycle and sprint planning. Bachelor’s degree in engineering, computer science, physics, math, or equivalent (Master’s or PhD preferred). P4, Senior Machine Learning Engineer - Basic Qualifications
7+ years of experience building applied machine learning products at scale. 3+ years of experience with deep learning frameworks such as Pytorch or TensorFlow. 4+ years of experience building production‑scale ML model hosting services. 2+ years of experience with LLMs, text generation models, or graph neural networks. 4+ years of experience with cloud platforms (AWS, GCP, etc.). Proven track record of leading, mentoring, and managing ML engineering teams. Bachelor’s degree in engineering, computer science, physics, math, or equivalent (Master’s or PhD preferred). Other Qualifications
Stay current on AI, LLMs, RAG, autonomous agents, and orchestration frameworks. Deep understanding of statistical analysis, unsupervised and supervised ML algorithms, and NLP for information retrieval or recommendation systems. Professional experience solving ambiguous, open‑ended problems and leading technical teams. Excellent interpersonal and communication skills to build relationships across teams. Pay Transparency
Annualized base salary ranges:
Primary Location (USA.CA.Pleasanton)
$230,400 – $345,600 USD;
Additional US Locations
$194,600 – $345,600 USD. Compensation may include bonus, commissions, stock grants, and other benefits. Flexible Work
Workday offers a flexible model: spend at least 50% of time each quarter in office or in the field, allowing for a hybrid schedule that balances collaboration and autonomy. Equal Opportunity
Workday is an Equal Opportunity Employer, including individuals with disabilities and protected veterans, and considers qualified applicants with arrest and conviction records pursuant to applicable Fair Chance law.
#J-18808-Ljbffr
Join Workday as a Senior/Principal Machine Learning Engineer, a key role in advancing AI‑driven solutions that shape the future of work. About the Team
Agent Factory is a small, senior, cross‑functional AI team focused on building production‑grade intelligent agents used by millions daily. The team owns end‑to‑end problem ownership and collaborates closely across product, engineering, and data science. About the Role
As a Senior/Principal Machine Learning Engineer you will design and build the core ML systems behind Workday’s next generation of AI agents. You’ll own model development, agent logic, orchestration layers, and the entire ML lifecycle—from data strategy and model design to deployment, monitoring, and continuous improvement. You’ll implement frameworks for LLM‑powered agents, including RAG pipelines, workflow orchestration, evaluation, and feedback loops, ensuring scalability, observability, and enterprise readiness. P5, Principal Machine Learning Engineer - Basic Qualifications
10+ years of experience building applied machine learning products at scale, including research, design, implementation, production, and evaluation. 4+ years of experience with deep learning frameworks such as Pytorch or TensorFlow. 6+ years of experience building production‑scale services that host ML models. 3+ years of experience working with large language models (LLMs), text generation models, or graph neural networks for real‑world use cases. 6+ years of experience with cloud platforms (AWS, GCP, etc.). Proven track record of leading, mentoring, and managing ML engineering teams, overseeing the development lifecycle and sprint planning. Bachelor’s degree in engineering, computer science, physics, math, or equivalent (Master’s or PhD preferred). P4, Senior Machine Learning Engineer - Basic Qualifications
7+ years of experience building applied machine learning products at scale. 3+ years of experience with deep learning frameworks such as Pytorch or TensorFlow. 4+ years of experience building production‑scale ML model hosting services. 2+ years of experience with LLMs, text generation models, or graph neural networks. 4+ years of experience with cloud platforms (AWS, GCP, etc.). Proven track record of leading, mentoring, and managing ML engineering teams. Bachelor’s degree in engineering, computer science, physics, math, or equivalent (Master’s or PhD preferred). Other Qualifications
Stay current on AI, LLMs, RAG, autonomous agents, and orchestration frameworks. Deep understanding of statistical analysis, unsupervised and supervised ML algorithms, and NLP for information retrieval or recommendation systems. Professional experience solving ambiguous, open‑ended problems and leading technical teams. Excellent interpersonal and communication skills to build relationships across teams. Pay Transparency
Annualized base salary ranges:
Primary Location (USA.CA.Pleasanton)
$230,400 – $345,600 USD;
Additional US Locations
$194,600 – $345,600 USD. Compensation may include bonus, commissions, stock grants, and other benefits. Flexible Work
Workday offers a flexible model: spend at least 50% of time each quarter in office or in the field, allowing for a hybrid schedule that balances collaboration and autonomy. Equal Opportunity
Workday is an Equal Opportunity Employer, including individuals with disabilities and protected veterans, and considers qualified applicants with arrest and conviction records pursuant to applicable Fair Chance law.
#J-18808-Ljbffr