腾讯云 DataBuddy-机器学习平台高级工程师
Core
Building end-to-end MLOps platforms and enterprise-grade feature stores to standardize AI R&D delivery and ensure high-performance model serving.
Role type
Senior Machine Learning Platform Engineer (MLOps)
Builds
Automated training pipelines, unified offline/online feature systems, and scalable model serving infrastructure.
Domain
Cloud computing, AI infrastructure, MLOps
Deliverable
production ML models
Required skills
MLOps, Feature engineering, Python, Go, Docker, Kubernetes, CI/CD, MLflow, Kubeflow, Airflow, PyTorch, TensorFlow, Redis, OSS/S3, MySQL, Ray, Spark, Flink
Preferred skills
None stated
Technologies
Feast, MLflow, Kubeflow, Airflow, Docker, Kubernetes, PyTorch, TensorFlow, Redis, OSS, S3, MySQL, Ray, Spark, Flink
Responsibilities
Build end-to-end MLOps workflows covering data, feature, training, versioning, evaluation, deployment, inference, and monitoring; Lead the implementation and optimization of enterprise feature platforms; Construct automated training pipelines for experiment tracking and version management; Engineer model containerization, gray release, and elastic scaling for high availability and low latency; Establish observability systems for data, feature, and model metrics to ensure stability.
Seniority
Senior, hands-on IC