AI ML Developer

Job Title: Sr. AI ML Developer

Experience Range: 8+ Years

Location: Hyderabad

Required Technical skill set: AI ML, Edge AI

Must-Have:

• 5+ years of hands-on development experience in AI/ML.
• Strong knowledge of ML libraries (TensorFlow Lite, PyTorch Mobile, ONNX).
• Experience with edge hardware platforms (e.g., Raspberry Pi, Jetson Nano, Coral Dev Board).
• Proficient in Python and C/C++.
• Familiarity with performance optimization techniques for models on edge.
• Experience with REST APIs, messaging protocols, or low-latency data streaming.
• Ability to perform predictive and statistical analysis from different data source
• knowledge and hands-on experience of building and deploying AI models on edge devices.
• knowledge of embedded systems, microcontrollers, or low-power compute devices.
• Experience with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines
• Experience with Image Processing, Computer Vision, NLP, Pattern Recognition, Machine Learning and Linear algebra.
• knowledge and exposure to model optimization techniques.
• Experience with AI accelerator frameworks

Good-to-Have:

• Familiarity with OpenCV, YOLO, or MobileNet for vision tasks.
• Knowledge of TinyML or microcontroller-based AI inference.
• Exposure to MLOps tools and versioning (MLflow, DVC).
• Understanding of security practices in edge deployments.
• Experience with edge analytics, anomaly detection, or predictive maintenance use cases.
• Exposure to deployment tool-chain like Intel EII, Nvidia Deep Stream, Qualcomm AI Hub, etc....
• Exposure to popular platforms such as Azure, AWS

Responsibility of the Role:

• Build and optimize AI/ML models for edge deployment.
• Develop edge inference pipelines using lightweight frameworks.
• Optimize models for resource-constrained environments (quantization, pruning).
• Integrate AI models into embedded or IoT platforms.
• Collaborate with cross-functional teams on data collection, preprocessing, and annotation.
• Implement software for real-time processing and decision-making at the edge.