MLOps Engineer building production ML infrastructure, pipelines, and monitoring for exacare ai’s post - acute care AI platform. Scaling reliable systems that help healthcare teams make safer placement decisions.
About the role
- Machine Learning Engineer designing and building ML systems for Workday's AI agents. Collaborating with cross-functional teams to integrate solutions and enhance product capabilities.
Responsibilities
- Design and build the core ML systems behind Workday’s next generation of AI agents
- Collaborate within a small, senior, cross-functional pod on models, agent logic, and orchestration layers
- Implement and evolve frameworks for LLM-powered agents, including RAG pipelines, workflow orchestration, evaluation, and feedback loops
- Partner closely with software engineers, product managers, and data scientists to integrate agents deeply into the Workday stack
- Stay hands-on with emerging techniques in agentic architectures
Requirements
- 4+ 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
- 3+ 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
- 3+ 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
- Workday Bonus Plan
- Annual refresh stock grants
- Flexible work arrangements
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