Model Deployment Engineer

ti Steps

3 - 5 years

4 - 6 Lacs

hyderabad chennai bengaluru

Posted:14 hours ago| Platform:

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Skills Required

cloud deployment gen artificial intelligence ai platform machine learning gcp deployment computer vision aws python kubernetes

Work Mode

Work from Office

Job Type

Full Time

Job Description

About the Role:

Model Deployment Engineer

Key Responsibilities:

Design, develop, and maintain end-to-end machine learning model deployment pipelines.
Collaborate with data scientists and ML engineers to productionize machine learning models.
Containerize machine learning models using Docker and orchestrate deployments using Kubernetes.
Implement and manage scalable model serving platforms such as TensorFlow Serving, TorchServe, Seldon Core, or MLflow.
Build and maintain APIs and microservices to expose model predictions to business applications.
Develop and maintain CI/CD pipelines tailored for ML workflows, ensuring automated testing, validation, and deployment of models.
Monitor deployed models for performance, latency, and accuracy; implement retraining triggers and rollback mechanisms.
Ensure security, compliance, and governance of ML deployment infrastructure.
Troubleshoot and resolve issues related to model deployment, scaling, and integration.

Preferred Skills:

Experience with feature stores and data versioning tools.
Knowledge of real-time and batch processing architectures.
Familiarity with security and compliance standards relevant to ML deployments.
Experience with distributed computing and scalable data pipelines.
Certifications related to cloud platforms or Kubernetes (CKA, AWS Certified ML Specialty).
Background in DevOps or SRE practices applied to ML systems.

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