À propos
As a Machine Learning Engineer on the AI Core team, you will develop tailored user experiences using advanced Agentic AI, LLMs, and RAG. You will collaborate with other engineers to deliver ML solutions across Workday’s product ecosystem and use current software and data engineering stacks to enable training, deployment, and lifecycle management of a variety of ML models – supervised and unsupervised. Additionally, you will develop and deploy new APIs and services with Docker and Kubernetes at scale, and leverage Workday’s computing resources on rich datasets to deliver transformative value to our customers. Responsibilities
Own exploration, design, and implementation of features for our sophisticated ML platforms, pipelines, and services. Be responsible for evaluation, scalability, and observability of these features. Apply machine learning techniques including LLMs and NLU to analyze large sets of HR and Finance‑related text data, and design and launch pioneering cloud‑based machine‑learning architectures. Stay up to date with advancements in AI, LLMs, RAG, autonomous agents, and orchestration frameworks to drive innovation. Serve as a technical role model for more junior engineers. Basic Qualifications
Bachelor’s (Master’s or PhD preferred) degree in engineering, computer science, physics, math or equivalent. 3+ years experience building applied machine‑learning products at scale, including product research, design, implementation, production, and evaluation. 3+ years professional experience with Python and supporting numeric libraries, and shipping production code and models. 3+ years professional experience with cloud computing platforms (e.g., AWS, GCP). Other Qualifications
3+ years professional experience building information retrieval systems and/or graph‑based recommendation systems. 3+ years hands‑on experience developing large language models (LLMs), text generation models, or graph‑based ML models for production, including data processing, fine tuning, deployment, and evaluation. 3+ years professional experience building services to host ML models at scale. 3+ years professional experience with machine‑learning frameworks & toolkits such as PySpark, Pytorch, TensorFlow, and Sklearn. 3+ years professional experience with data engineering and wrangling using Pandas, PySpark, Kubernetes, Docker. Deep understanding of statistical analysis, supervised and unsupervised ML algorithms, and NLP for IR and recommendation use cases. Professional experience independently solving ambiguous problems and technically leading teams. Workday Pay Transparency Statement
The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on location. As part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role‑specific commission/bonus, and annual stock grants. Each candidate’s compensation offer will be based on multiple factors including geography, experience, skills, job duties, and business need. Primary Location: USA.CO.Boulder Primary Location Base Pay Range: $143,400 USD – $215,200 USD Additional US Locations Base Pay Range: $136,200 USD – $240,000 USD Our Approach to Flexible Work
With Flex Work, we combine in‑person time and remote work. We spend at least half (50%) of our time each quarter in the office or in the field with customers, prospects, and partners, depending on role, allowing you freedom to create a flexible schedule while making intentional time together. Equal Opportunity Employer
Workday is an Equal Opportunity Employer, including individuals with disabilities and protected veterans. Pursuant to Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records. We are committed to providing an accessible and inclusive hiring experience where all candidates can demonstrate their skills. If you require assistance or accommodation, please email accommodations@workday.com.
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Compétences linguistiques
- English
Avis aux utilisateurs
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