Position: Senior MLOps Engineer
Location: India (Hybrid)
Experience: 6 Years
Relevent Exp : 4+ Years

About BinQle
BinQle is a global delivery and execution partner supporting enterprises across the US, India, Singapore and Australia. We specialize in structured hiring, managed teams, and long-term delivery support.

Role Summary:
Own the deployment, monitoring, and lifecycle management of production ML models for telecom network operations automation. Collaborate with data scientists and network operations teams to ensure robust AI/ML delivery and set engineering standards for MLOps.

What Youll Do:
Design and maintain end-to-end ML pipelines covering training, validation, deployment, and retraining across multiple customer settings
Build and manage CI/CD workflows for ML models with automated testing, evaluation gates, and staged rollout strategies
Implement model monitoring to detect data drift, performance degradation, and distribution shifts in production
Manage multi-tenant model deployments with version control, workplace isolation, and rollback capability




Integrate ML model outputs with telecom OSS/BSS systems and real-time network data streams
Define retraining triggers based on drift signals or data volume thresholds and automate retraining workflows
Establish MLOps standards covering experiment reproducibility, model lineage, versioning, and governance
Lead design reviews, mentor engineers, and contribute to the AI/ML platform roadmap

What We re Looking For (Must-Haves):
-1. Overall experience is 6 years and relevent is 4 years in MLOps.
Solid hands-on experience in LLM deployment
Basic knowledge of Kubernetes
Experience with GCP or Azure
As per requirement
As per requirement

Good to Have (Optional - only if mentioned):
Cloud experience

Qualifications:
As per requirement

Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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