About the role

Role Overview

As a Senior MLOps Engineer at Twin Health, you will help integrate machine learning with healthcare technology by building and operating production-ready AI/ML systems. You’ll architect robust ML infrastructure, improve existing healthcare ML solutions, and collaborate with Data, Infra, and ML engineering teams.

Key Missions & Responsibilities

Architect, design, and build efficient and reliable AI/ML systems for production.
Focus on backend distributed systems and microservices, ensuring system accuracy.
Lead cross-functional initiatives end-to-end (scoping, timelines, dependencies) and drive alignment across Data, Infra, and ML Engineering.
Collaborate with AI/ML engineers to optimize:
- Model training workflows
- Real-time inference pipelines
- Monitoring and troubleshooting
Ensure operational excellence of ML systems.
Mentor and share knowledge with the team.

Requirements

Self-driven, able to handle multiple projects and collaborate effectively.
Strong experience with complex, distributed, high-scale ML application architectures.
5+ years of industry experience; Bachelor’s or Master’s in CS/Engineering or related field.
Strong MLOps knowledge plus data structures and software design principles.
Python proficiency; experience with Java or Go.

Nice to Have

Experience implementing applications using LLMs and GenAI.
SQL/NoSQL databases and big data frameworks like Spark.
Experience deploying scalable ML models using Docker and Kubernetes; microservices architecture.

Location / Work Style

Full remote

About Twin Health

Twin Health is a healthcare technology company that applies machine learning to improve healthcare solutions. The team builds and operates machine learning platforms and production-grade AI/ML systems in a healthcare context.

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