About the Role

We are seeking highly skilled Machine Learning Engineers to contribute to a cross-functional team building transformative AI agents for HR & Finance. This role is crucial in implementing tooling strategies, staying informed about industry trends, and ensuring our AI-driven solutions integrate effectively within the Workday stack. You will be responsible for implementing AI frameworks, contributing to agent workflow orchestration, utilizing LLMs, agent frameworks, and enterprise AI to design and develop scalable, reliable and trusted AI agents for both HR and Finance.

Key Responsibilities:

• Collaborate with a team of innovative engineers to deliver AI-powered agents that integrate deeply into HR and Financial workflows, accelerating intelligent decision making.
• Develop relationships with software engineers, machine learning engineers, and data scientists on partner teams
• Apply understanding of the AI system lifecycle, including problem definition, data acquisition, model training, system integration, and validation.
• Implement and integrate AI tools, frameworks, and platforms to ensure scalability, efficiency, and compliance.
• Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation.
• Work with product, engineering, and data science teams to implement AI-based automation solutions that enhance HR and financial operations.
• Collaborate with external AI vendors, cloud providers, and open-source communities to integrate best-in-class technologies into our AI stack.
• Contribute to establishing monitoring, feedback loops, and continuous learning mechanisms to improve agent performance over time.

About You

Basic Qualifications:

• 3+ years experience as a member of a data science, machine learning / AI 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
• 2+ years of professional experience with Python, Java, C++, etc. and supporting numeric libraries, with experience in shipping production code and models
• 1+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow, Huggingface
• 1+ years of professional experience in building services to host machine learning models in production at scale with cloud computing platforms (e.g. AWS, GCP, etc.)
• 1+ years of professional experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases
• Bachelor’s (Master’s or PhD preferred) degree in engineering, computer science, physics, math or equivalent

Other Qualifications:

• Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation
• 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
• Excellent interpersonal and communication skills, with the ability to build strong relationships across teams and stakeholders
• Proven track record of successfully leading, mentoring, and/or managing ML Engineering teams, taking ownership of development lifecycle and sprint planning; fostering a culture of collaboration, transparency, innovation, etc.

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 candidate’s 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 Workday’s comprehensive benefits, please click here.

Our Approach to Flexible Work
 

With Flex Work, we’re 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 you'll 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.