About the RoleWe are looking for an MLOps Engineer with 3–5 years of experience (including 0–3 years in AI/ML engineering) to help build, deploy, and maintain our machine learning solutions. This role focuses on deploying AI models to edge devices and integrating them with our C++ backend systems. You will work closely with ML, C++, and embedded engineering teams to ensure smooth and reliable production operations.Key Responsibilities- Deploy and optimize ML models on edge devices (ARM boards, Jetson, etc.). - Convert and package models for C++ integration (ONNX, TensorRT, TFLite). - Automate ML workflows including training, testing, and deployment. - Build and maintain CI/CD pipelines for Python and C++ components. - Monitor model performance on devices—latency, drift, accuracy, resource usage. - Support data pipelines for collecting field data from edge devices. - Manage model versioning, tracking, documentation, and release processes.Required Skills- Strong Python skills and working knowledge of C++ integration. - Experience with deploying models on edge/embedded hardware. - Familiarity with ONNX Runtime, TensorRT, TFLite, or similar optimization tools. - Experience with CI/CD tools (GitHub Actions, GitLab CI, Jenkins). - Understanding of ML workflows and model lifecycle. - Good communication and documentation skills. - Experience with real-time systems or embedded environments. - Knowledge of lightweight orchestrators. - Experience building telemetry/monitoring for edge devices.What You Will Achieve- Reliable, fast, hardware-optimized ML deployments on edge devices. - Smooth integration of ML models with C++ backend systems. - Automated, repeatable, and stable ML operations across the full lifecycle.
Job Title
MLOps Engineer