FI
Data Science project analyzing price trends for commodities using AI at Fraunhofer Institute. Collaborating on Data Analytics projects to develop predictive models and understanding price formation.
About the role
- Machine Learning Engineer in Workday's AI Platform team developing systems for agent observability and optimization. Solving complex challenges with innovative ML solutions and advanced algorithms in a collaborative environment.
Responsibilities
- Develop algorithms for automated node-level optimization within agent graphs
- Architect Evaluation Pipelines using Kubeflow on the cloud
- Build a Python-native framework for complex metrics
- Implement real-time evaluation and A/B testing frameworks
- Drive the design of metrics warehouse for actionable insights
- Design, build, and deploy sophisticated AI agents
- Own the entire ML lifecycle for high-quality, scalable deployment
Requirements
- 3+ years of professional experience as a Machine Learning Engineer
- Demonstrated experience in building and evaluating AI agents
- Expertise in prompt engineering and optimization
- Proven understanding of statistical analysis and machine learning algorithms
- Solid understanding of A/B testing and experimental design
- Proficiency in modern ML frameworks (e.g. PyTorch, TensorFlow)
- Expert-level Python skills
- Experience with multi-threading and asynchronous call patterns
- Experience designing 'Agent-in-the-loop' systems
- Knowledge of MLOps and cloud services (e.g. AWS, GCP, Azure)
Benefits
- Workday Bonus Plan
- role-specific commission/bonus
- annual refresh stock grants
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