Project Description
Our client, a leading manufacturer of high-end household appliances, is expanding into new smart product lines. As part of this strategic initiative, a large-scale global program is being implemented across the company's IP portfolio. This includes the development of new embedded software, enhancements to cloud infrastructure.
Skills Required
- Bachelor's Degree or Master's degree in Computer Science, Software Engineering, or related field.
- 3 to 10+ years of experience developing computer vision applications/algorithms
- Participate in at least 2 image processing/computer vision projects, and 1 of them productized
- Image processing / computer vision background/understanding
- Strong C/C++ experience
- Experience with OpenCV and ML frameworks such as Pytorch, TensorFlow, TensorFlow Lite
- Deep understanding of neural network architectures
- Experience deploying ML models on embedded/edge devices
- Experience to work with embedded devices in C++ on Linux
- Decent understanding geometry 2D/3D and algebra.
- Desire to learn new technologies
- Desire to follow test driven development (in CV/ML too)
Responsibilities
- Designed and implemented advanced computer vision and image processing pipelines optimized for real-time consumer devices.
- Collaborated with ISP, sensor, and perception teams to define image quality requirements and tune outputs for downstream AI and UX performance.
- Developed and trained custom ML models for visual recognition, enhancement, and scene understanding; optimized for edge deployment via quantization, pruning, and distillation.
- Implemented performance-critical algorithms in modern C++ across embedded platforms, optimizing latency, power, memory, and thermal constraints.
- Integrated inference engines (TensorRT, TFLite, ONNX Runtime) and ML modules into production pipelines; profiled and optimized across CPU/GPU/NPU/DSP.
- Defined and tracked KPIs (FPS, accuracy, power usage, startup time) while ensuring robust unit testing, automated validation, and production readiness.
- Mentored engineers, reviewed architecture/design proposals, and supported product bring-up for mass production.
(ref:hirist.tech)
