AI/ML Developer (Telecom Network Operations)

Solution Engineer - AI/ML Developer

Experience: 2+ years

Annual Salary Budget: 8-10 LPA

No of Positions - 1

Shift Timing: General

Mode of Work : Gurgaon / Hyderabad . However, remote option can be considered, provided the candidate is open to working from the office whenever required

Expected Start Date Immediate preferred

Solution Engineer - AI/ML Developer (Telecom Network Operations)

Overview:

We are seeking a motivated AI/ML Developer with 2+ years of experience in developing Artificial Intelligence and Machine Learning solutions, with a focus on computer vision and image analysis for Telecom Network Operations. The candidate will contribute to the end-to-end development, training, enhancement, and deployment of AI models and their integration with enterprise applications.

This position requires close collaboration with cross-functional teams to support network Planning and operations teams and providing solutions network planning, KPIs Management reporting, operations support and network analysis. The role also involves creating APIs and web services, optimizing existing / enhancing existing tools/applications improve performance, supporting data Management and migrations, and leveraging modern AI, cloud, and web mapping frameworks.

Responsibilities:

• Develop and implement AI/ML solutions using Python for Telecom Network Operations use cases.
• Build and enhance computer vision and object detection models, including Mask R-CNN and other relevant deep learning algorithms.
• Perform image analysis to identify, classify, and detect telecom network assets, infrastructure, defects, or operational issues.
• Work with customer-specific datasets, including:
• Data collection and preparation
• Data cleaning and preprocessing
• Image annotation and augmentation
• Feature engineering and analysis
• Train, evaluate, fine-tune, and optimize AI/ML models based on business and customer requirements.
• Develop end-to-end AI model development pipelines, from data preparation through model deployment.
• Build and expose trained AI models as REST APIs/services for consumption by third-party and enterprise systems.
• Integrate AI/ML solutions with existing Telecom OSS, network management, GIS, or other operational platforms.
• Work with RAG (Retrieval-Augmented Generation) techniques for AI applications involving enterprise knowledge and documentation.
• Apply appropriate Machine Learning algorithms based on business problems and available data.
• Use Python libraries such as NumPy and Pandas for data processing, analysis, and model preparation.
• Work with modern Large Language Models (LLMs) such as:
• OpenAI
• Google Gemini
• Anthropic Claude
• Llama etc.
• Develop and consume RESTful APIs and support integration with external applications.
• Participate in technical discussions with customers and internal teams.
• Understand customer business requirements and translate them into appropriate AI/ML technical solutions.
• Prepare and maintain technical documentation, including solution design, model architecture, APIs, and implementation details.

Qualifications & Technical skills

• Bachelor’s degree Computer Science, or a related field.
• 2+ years of overall experience in AI/ML or software development.
• Strong programming skills in Python.
• Knowledge of Machine Learning and Deep Learning algorithms.
• Hands-on exposure to Object Detection and Image Analysis.
• Knowledge of Mask R-CNN or similar object detection/segmentation models.
• Experience with:
• NumPy
• Pandas
• Data preprocessing and analysis
• Understanding of RAG architecture and concepts.
• Knowledge of LLMs, including OpenAI, Gemini, and/or Claude.
• Experience developing and exposing applications or models through REST APIs.
• Basic understanding of model training, testing, evaluation, and fine-tuning.
• Understanding of the complete AI/ML lifecycle:
• Data → Training → Evaluation → Fine-tuning → Deployment → API Integration

Preferred skills:

• Experience or knowledge of Telecom Network Operations.
• Understanding of telecom infrastructure such as:
• Towers and poles
• Fiber networks
• Network equipment
• Field infrastructure
• Experience with image annotation tools and datasets.
• Exposure to AI frameworks such as PyTorch or TensorFlow.
• Knowledge of cloud-based AI services or model deployment platforms.
• Familiarity with MLOps concepts is an added advantage.
• Experience integrating AI …