Mandatory Skills
- 5+ Years of relevant industry experience
- Strong understanding of machine learning frameworks such as TensorFlow, PyTorch, scikit-learn.
- Experience in designing and executing automated test frameworks for ML/DL systems.
- Familiarity with DevOps tools like Docker, Kubernetes, Jenkins, GitLab CI.
- Exposure to ML model optimization for edge devices (e.g., TensorRT, OpenVINO, Edge TPU).
- Knowledge of MLOps practices, including model versioning and deployment workflows.
- Understanding of natural language processing and Tiny LLMs is a plus.

Key Responsibilities
- Develop and execute test strategies for machine learning, deep learning, and Tiny LLM models running on IoT edge devices.
- Validate model accuracy, robustness, and scalability under real-world IoT data conditions.
- Design automated frameworks to test data pipelines, feature extraction, inference performance, and edge/cloud integration.




- Ensure seamless integration of ML/DL modules into the IoT platform software stack (firmware, middleware, connectivity, and cloud APIs).
- Collaborate with ML developers to ensure models meet production-grade quality standards.
- Work with DevOps engineers to integrate ML model validation into CI/CD workflows.

Requirements:
- Solid understanding of machine learning frameworks such as TensorFlow, PyTorch, scikit-learn.
- Experience in designing and executing automated test frameworks for ML/DL systems.
- Familiarity with DevOps tools like Docker, Kubernetes, Jenkins, GitLab CI.
- Exposure to ML model optimization for edge devices (e.g., TensorRT, OpenVINO, Edge TPU).
- Knowledge of MLOps practices, including model versioning and deployment workflows.
- Understanding of natural language processing and Tiny LLMs is a plus

📌 Ai ML Engineer (Hyderabad)
🏢 Triad Square Infosec
📍 Hyderabad