Lead ML Engineer

Lead ML Engineer Lead the end-to-end design, development, and deployment of machine learning solutions addressing telecom industry challenges. Mentor engineering teams while driving integration of telecom domain expertise into ML projects focused on wireline, wireless, real-time network analysis, churn, and emerging telecom technologies. Key Responsibilities:Lead ML project delivery including data collection, feature engineering, model development, and production deployment for telecom applications. Architect scalable ML systems optimized for processing large volumes of telecom data (sites, interfaces, NQES, SINR).Mentor junior engineers on ML best practices, telecom domain specifics, and large-scale system design. Collaborate with data scientists, product managers, and business teams to align ML projects with telecom business goals. Enforce coding standards, testing, and documentation in telecom ML workflows. Research and incorporate latest telecom trends and technologies into ML systems. Skills and Requirements:Extensive experience with ML frameworks (Tensor Flow, PyTorch) and distributed data platforms (Spark, Hadoop) in telecom contexts. Strong leadership and project management experience managing telecom-focused ML teams. Expertise in cloud ML services (AWS Sage Maker, GCP AI Platform) and container orchestration (Kubernetes).Deep understanding of telecom domain concepts and ability to translate them into scalable ML architectures. Composer, Data Proc over GCP, Vertex. AI, Big Query, Teradata Understanding H2O is a plus