Machine Learning Engineer, Workday

• In addition to contributing to feature and service development, you must have an approach of continuous improvement, passion for quality, scale, and security
• Ou must be curious and prepared to question or challenge choices and practices where they don't make sense to you or could be improved
• You also should have a product approach and strong intuition around how ML can drive a better customer experience
• Lastly, a strong sense of ownership and teamwork are essential to succeed in this role
• Bachelor’s (Master’s or PhD preferred) degree in engineering, computer science, physics, math or equivalent
• 3+ years of professional experience in building information retrieval systems and/or graph-based recommendation systems
• 3+ years of hands-on professional experience in developing text-based or graph-based machine learning models for production, including data processing, model fine-tuning, model deployment and model evaluation
• 2+ years of professional experience in building services to host machine learning models in production at scale
• 2+ years of professional experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases
• 2+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow, and Sklearn
• 2+ years of professional experience with data engineering and data wrangling using e.g. Pandas and PySpark and other industry tools used to build scalable machine learning systems, such as Kubernetes and Docker
• 2+ years of professional experience with cloud computing platforms (e.g. AWS, GCP, etc.)
• Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms, and natural language processing for information retrieval and/or recommendation system use cases

Desirable

• We are developing ML-powered Information Retrieval, Recommendation and Agentic services and platforms to modernize and simplify user interactions with Workday
• As a machine learning engineer, you will help develop tailored user experiences using advanced Agentic AI, LLMs, Knowledge Graphs, personalization, and predictive analysis
• You will collaborate with other engineers to deliver ML solutions across Workday’s product ecosystem and utilize current software and data engineering stacks to enable training, deployment, and lifecycle management of a variety of ML models; supervised and unsupervised, and agentic AI powered by LLMs
• Additionally, you will develop and deploy new APIs/microservices using docker/kubernetes at scale and leverage Workday’s vast computing resources on rich datasets to deliver transformative value to our customers. Sound like your kind of challenge?
• Own exploration, design and execution of advanced ML models, algorithms and frameworks that deliver value to our users
• Apply machine learning techniques including LLMs, knowledge graphs, deep learning including generative models, natural language understanding, topic modeling, GNNs and named entity recognition to analyze large sets of HR and Finance-related text data, and design and launch pioneering cloud based machine learning architectures
• Own the performance, scalability, metric based deployed evaluation, and ongoing data driven enhancements of your products
• Keep abreast of the latest advancements in NLP research, techniques, and tools and apply this knowledge onto ML Features