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Lead Data Science & ML Ops - ML migration

0 years

0 Lacs

chennai tamil nadu india

Posted:1 day ago| Platform: Linkedin logo

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Skills Required

data ml migration design architecture scalability management video strategies integration deployment monitoring governance devops security compliance reliability leadership tensorflow pytorch mlflow composer aws gcp analytics python containerization docker orchestration communication hadoop

Work Mode

On-site

Job Type

Full Time

Job Description

Overview

Job Summary: -

Design and oversee the architecture of ML, data science, and MLOps systems tailored for large-scale telecom environments. Ensure scalability, robustness, and efficient lifecycle management of models addressing telecom-specific challenges.

Responsibilities

Key Responsibilities: -

  • Architect end-to-end ML and DS solutions incorporating telecom domain knowledge (wireline, wireless, NQES, churn, SINR, Video on Demand, FWA).
  • Define and implement MLOps strategies for continuous integration, deployment, monitoring, and governance of telecom ML models.
  • Collaborate with data scientists, engineers, and DevOps teams to streamline workflows and infrastructure for telecom data pipelines and models.
  • Evaluate and recommend tools, frameworks, and platforms optimized for telecom ML and DS projects.
  • Ensure security, compliance, scalability, and reliability of telecom ML systems.
  • Provide technical leadership and mentorship in both architecture and telecom domain best practices.

Requirements

Skills and Requirements: -

  • Deep expertise in ML frameworks (TensorFlow, PyTorch), MLOps tools (Kubeflow, MLflow, Composer), and cloud platforms (AWS, GCP, Azure).
  • Strong knowledge of telecom domain data structures and analytics requirements.
  • Experience designing scalable distributed systems and data architectures for telecom datasets.
  • Proficiency in Python, containerization (Docker), and orchestration (Kubernetes).
  • Excellent analytical, architectural, problem-solving, and communication skills.
  • Ability to bridge technical and telecom domain knowledge effectively.
  • Understanding the Hadoop & GCP Bigdata architecture - DataProc, Vertex.AI, BigQuery, Composer,Jenkins,
Constructing the Common packages like products / bundles is an advantage

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