Master Thesis focusing on developing machine learning models for lithium - ion cell sorting at Fraunhofer LBF. Involvement in innovative projects addressing circular economy in battery recycling.
About the role
- Machine Learning Engineer designing and building core ML systems behind Workday's AI agents. Collaborating within cross-functional teams to integrate AI solutions into the Workday platform.
Responsibilities
- Design and build the core ML systems behind Workday’s next generation of AI agents
- Own how models, agent logic, and orchestration layers come together in production
- Implement and evolve frameworks for LLM-powered agents, ensuring solutions are scalable, observable, and enterprise-ready
- Partner closely with software engineers, product managers, and data scientists to integrate agents deeply into the Workday stack
Requirements
- 5+ years experience as a member of a data science, machine learning engineering, or other relevant software development team building applied machine learning products at scale
- 2+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow
- 2+ years of professional experience in building services to host machine learning models in production at scale
- 2+ years of demonstrated experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases
- 2+ years of proven experience with cloud computing platforms (e.g. AWS, GCP, etc.)
- Bachelor’s (Master’s or PhD preferred) degree in engineering, computer science, physics, math or equivalent
Benefits
- Health insurance
- Flexible work arrangements
- Professional development opportunities
- Workday Bonus Plan or role-specific commissions/bonuses
- Annual refresh stock grants
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