Sr. Machine Learning Ops Engineer
Core
Operationalizing machine learning and Generative AI solutions at scale, focusing on deploying, standardizing, and maintaining production-ready ML and agentic AI systems.
Role type
Senior MLOps Engineer
Builds
Production-ready ML and agentic AI systems, end-to-end pipelines (CI/CD, monitoring, alerting), and observability frameworks.
Domain
Healthcare / Generative AI / Machine Learning Operations
Deliverable
production ML models
Required skills
ML model deployment, CI/CD pipelines, GenAI/agentic AI frameworks, model observability, cloud platforms (AWS/Azure/GCP), cost optimization, secure deployment
Preferred skills
Databricks ecosystem, LangChain/LangGraph/Semantic Kernel, GenAI cost optimization, secure enterprise applications, healthcare/regulated environment experience
Technologies
LangChain, LangGraph, Semantic Kernel, Databricks, Okta, AWS, Azure, GCP
Responsibilities
Lead deployment and operationalization of ML models and GenAI solutions; Partner with Data Scientists to automate high-impact model use cases; Define and enforce standardized deployment patterns; Own KTLO operations including health monitoring and logging; Design pipelines for batch, real-time, and event-driven inference; Establish observability frameworks; Drive cost and performance optimization; Partner with architecture, compliance, and governance teams.
Seniority
Senior, hands-on IC