Description

You will lead the engineering, development, and delivery of ML models using real-time network data to drive insights for Planning, Engineering, Operations, and Assurance groups.

This role is hybrid.

Responsibilities

• Engineer and deploy ML models that enable data-driven decision making.
• Design AI platform services including machine learning engines, in-memory computing, and streaming systems.
• Drive the technical roadmap and guide the implementation of new data-driven business solutions.
• Coordinate implementation across development teams to ensure system performance, security, scalability, and availability.

Required Skills

• 14+ years of relevant work experience.
• 3+ years of experience with advanced machine learning and deep learning models, specifically RNN, LSTM, and Graph Neural Networks (GNN).
• 3+ years of experience in modern data mining and data science techniques, including regressions, decision trees, ensemble algorithms, neural networks, time series analytics, clustering, anomaly detection, and text analytics.
• 2+ years of experience developing and deploying products using Docker, Kubernetes, and containerization technology.
• Proficiency in Python and at least one object-oriented programming language such as Java, Golang, or C.
• Expertise in developing large-scale, enterprise-class distributed systems requiring high availability, low latency, and strong data consistency.
• Proficient data wrangling skills using Python and SQL.
• Experience with Big Data and analytics leveraging Hadoop, Spark, and MapReduce.

Preferred Skills

• Background in the telecom domain.
• Practical experience with NoSQL data platforms (e.g., Druid, Cassandra) and caching technologies like Redis.

Key Skills

Education

Any Graduate