For Machine Learning

Hiring: ML Engineer – Telecom AI Solutions

Location: Bangalore,

Type: Full-Time

Company: GTS Techlabs

About GTS Techlabs

GTS Techlabs designs and develops innovative telecom and communication products to enhance customer communication experiences. With strong expertise in voice and messaging solutions, we ensure regulatory compliance and robust security. Our advanced platforms and data capabilities help enterprises derive insights for smarter marketing and customer service strategies. We also empower telecom

operators with AI/ML-driven fraud management systems to predict, prevent, and mitigate security threats.

The Role

We are looking for a skilled ML Engineer to build intelligent systems for fraud detection and traffic filtering in telecom networks. You will play a key role in developing AI-driven solutions for SMS Firewall platforms using machine learning, anomaly detection, and real-time analytics.

What You'll Do • Model Development: Design, implement, and deploy ML models to detect spam,

fraud, and grey routes in SMS and Voice traffic. • Anomaly Detection: Build real-time anomaly detection and predictive analytics

systems. • Big Data Processing: Work with Kafka, Spark, Flink, and Hadoop for large-scale data

processing. • Data Engineering: Preprocess, clean, and normalize structured and unstructured

telecom datasets. • Model Optimization: Deploy and optimize models using TensorFlow, PyTorch, or Scikitlearn. • Security & Compliance: Ensure data security, regulatory compliance, and model

interpretability. • Collaboration: Work closely with Product, Engineering, and Operations teams.

What We're Looking For • Experience: 3–5 years of relevant experience in Machine Learning / AI roles. • ML & AI Skills: Supervised & unsupervised learning, anomaly detection, NLP. • Programming: Strong Python skills (TensorFlow, PyTorch, Scikit-learn), SQL. • Data Processing: Pandas, NumPy, Spark for large-scale data processing. • Big Data & Streaming: Kafka, Spark, Hadoop, Flink. • Databases: MySQL, PostgreSQL, MongoDB, Cassandra. • Model Deployment: Docker, Kubernetes, AWS SageMaker, Azure ML, Google AI

Platform. • Education: B.Tech / M.Tech / MCA or equivalent.

Preferred Qualifications • Experience with MLOps and CI/CD for ML models (MLflow, Kubeflow, Airflow). • Exposure to cloud-based AI platforms (AWS, Azure, Google Cloud). • Certifications in AI/ML, Data Science, or Telecom Security