Machine Learning Engineer III

Your work days are brighter here.

Were obsessed with making hard work pay off for our people our customers and the world around us. As a Fortune 500 company and a leading AI platform for managing people money and agents were shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join youll feel it. Not just in the products we build but in how we show up for each other. Our culture is rooted in integrity empathy and shared enthusiasm. Were in this together tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether youre building smarter solutions supporting customers or creating a space where everyone belongs youll do meaningful work with Workmates whove got your return well give you the trust to take risks the tools to grow the skills to develop and the support of a company invested in you for the long haul. So if you want to inspire a brighter work day for everyone including yourself youve found a match in Workday and we hope to be a match for you too.

About the Team

About the Role

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 Workdays 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/services using Docker/Kubernetes at scale and leverage Workdays vast computing resources on rich datasets to deliver transformative value to our customers. Sound like your kind of challenge

You are a strong technical leader with deep Python expertise and solid software engineering skills capable of writing beautiful well-designed code while delivering solutions efficiently. Specifically you will:

• 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 natural language understanding 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

About You

Basic Qualifications:

• Bachelors (Masters or PhD preferred) degree in engineering data/computer science physics math or equivalent

• 3 yrs experience as a member of a data science machine learning engineering or other relevant software development team building applied machine learning products at scale including taking products through applied research design implementation production and production-based evaluation

• 3 years of professional experience with Python and supporting numeric libraries with experience in shipping production code and models

• 3 years of professional experience with cloud computing platforms (e.g. AWS GCP etc.)

Other Qualifications:

• 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 large language models (LLMs) text generation models or graph-based machine learning models for production including data processing model fine-tuning model deployment and model evaluation

• 3 years of professional experience building services to host machine learning models in production at scale

• 3 years of professional experience in machine learning and deep learning frameworks & toolkits such as PySpark Pytorch TensorFlow and Sklearn

• 3 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

• Deep understanding of statistical analysis unsupervised and supervised machine learning algorithms and natural language processing for information retrieval and/or recommendation system use cases

• Professional experience in independently solving ambiguous open-ended 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 work location. As a part of the total compensation package this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidates compensation offer will be based on multiple factors including but not limited to geography experience skills job duties and business need among other things. For more information regarding Workdays comprehensive benefits please click here.

Additional Considerations:

Our Approach to Flexible Work

With Flex Work were combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections maintain a strong community and do their best work. We know that flexibility can take shape in many ways so rather than a number of required days in-office each week we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers prospects and partners (depending on role). This means youll have the freedom to create a flexible schedule that caters to your business team and personal needs while being intentional to make the most of time spent together. Those in our remote home office roles also have the opportunity to come together in our offices for important moments that matter.

Pursuant to applicable Fair Chance law Workday will consider for employment qualified applicants with arrest and conviction records.

Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.

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