Machine Learning /MLOps Engineer
Core
Design, build, and maintain scalable MLOps infrastructure, tools, and processes for continuous integration, delivery, and training of machine learning models.
Role type
Mid-senior MLOps Engineer
Builds
Scalable MLOps pipelines, cloud infrastructure for real-time and batch ML models, model monitoring systems, and reusable automation tooling.
Domain
Internet Gaming / MLOps
Deliverable
production ML models
Required skills
Python, Terraform, GCP, containerization, CI/CD pipelines, ML experiment tracking, model registry, feature stores, SQL, system design
Preferred skills
GCP Vertex AI, LLM deployment at scale
Technologies
Python, Terraform, GCP, Vertex AI
Responsibilities
Design and implement scalable MLOps pipelines for model training, testing, deployment, and monitoring; Build and manage cloud infrastructure to host and serve ML models; Establish robust model monitoring and alerting systems; Collaborate with data scientists to ensure production readiness and code optimization; Develop high-quality, reusable MLOps tooling; Drive automation initiatives for model deployment; Troubleshoot production issues and perform root cause analysis.
Seniority
Mid-senior, hands-on IC
