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
- Principal Machine Learning Engineer designing the core ML systems for AI agents at Workday. Collaborating in cross-functional teams to integrate ML solutions into the 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
- Stay hands-on with emerging techniques in agentic architectures
Requirements
- 10+ years experience as a member of a data science or machine learning engineering team building applied machine learning products at scale
- 4+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow
- 6+ years of professional experience in building services to host machine learning models in production at scale
- 3+ years of demonstrated experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases
- 6+ years of proven experience with cloud computing platforms (e.g. AWS, GCP)
- Proven track record of successfully leading, mentoring, and/or managing ML Engineering teams
- Bachelor's (Master’s or PhD preferred) degree in engineering, computer science, physics, math or equivalent
Benefits
- Workday Bonus Plan or role-specific commission/bonus
- Annual refresh stock grants
- Flexible work arrangements
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