Job Description: Staff Software Engineer
Role Overview We are seeking an experienced technology professional (8–10 years) with an engineering background (B.Tech / Masters) and strong expertise in Edge Computing, Edge AI, IoT, and Cloud integration. This role combines hands‑on technical leadership with strategic oversight, focusing on deploying AI/ML models at the edge, enabling anomaly detection and predictive maintenance, and integrating IoT devices with cloud platforms for scalable analytics.
Key Responsibilities
- Design and deploy Edge AI solutions for anomaly detection and predictive maintenance.
- Optimize and run AI/ML models at the edge on constrained devices for real‑time insights.
- Manage model lifecycle — training, validation, deployment, monitoring, and retraining.
- Continuously fine‑tune models to adapt to evolving data patterns and maintain accuracy.
- Validate third‑party connectors, gateways, and converters to ensure reliability in edge deployments.
- Integrate IoT devices with edge/cloud platforms (Azure, AWS, GCP) for secure pipelines and scalable analytics.
- Provide technical leadership and mentor teams on best practices in Edge AI and IoT.
Qualifications
- 8–10 years of experience in IoT, Edge Computing, or Cloud‑based analytics roles.
- Engineering degree (B.Tech / Masters) in Computer Science, Electronics, Electrical, or related fields.
- Proven expertise with Edge Computing platforms (Azure IoT Edge, AWS Greengrass, NVIDIA Jetson, etc.).
- Strong knowledge of AI/ML frameworks (TensorFlow Lite, PyTorch Mobile, ONNX Runtime) and deployment on constrained devices.
- Hands‑on experience with IoT protocols (MQTT, CoAP, Modbus, OPC UA) and device integration.
- Practical exposure to cloud services for IoT and analytics (Azure IoT Hub, AWS IoT Core, Google Cloud IoT).
- Demonstrated success in predictive maintenance and anomaly detection projects.
Preferred Attributes
- Experience with containerization/orchestration for edge workloads (Docker, Kubernetes at the edge).
- Knowledge of hybrid cloud‑edge architectures for scalable IoT deployments.
- Strong communication skills to bridge technical detail with executive‑level clarity.
- Collaborative mindset with proven ability to lead teams and drive adoption of edge/cloud solutions.