Senior ML Engineer
Tasks
- Deploy models using TensorRT ONNX Runtime TFLite OpenVINO and CoreML
- Develop CNN object detection models
- Develop deployment pipelines for edge devices
- Develop face detection models
- Document training optimization and deployment processes
- Estimate sprint tasks for optimization and deployment
- Implement pruning quantization and knowledge distillation
- Integrate vision models into products
- Lead scrum team for production readiness
- Optimize inference performance for resource constraints
- Optimize models for embedded inference
- Profile latency throughput and memory usage
Perks/Benefits
- Corporate English Course
- Corporate events
- Corporate lunch
- Flexible working hours
- Necessary equipment
- Online courses
- Paid Coworking
- Paid vacation
- Professional study support
- Remote work
- Sick leave
- Soft Skills Clubs
- Sports coverage
- Team building
- VIP medical insurance
Skills/Tech-stack
C++ | Computer Vision | Convolutional Neural Networks | Coral Edge TPU | CoreML | Edge AI | Edge TPU | Embedded AI | Face detection | Knowledge Distillation | Latency optimization | Memory Optimization | Model Acceleration | Model Compression | NVIDIA Jetson | Neural Networks | ONNX Runtime | Object Detection | OpenVINO | Performance Profiling | Pruning | Python | Qualcomm Snapdragon | Quantization | Raspberry Pi | TFLite | TensorRT | Throughput Optimization
Education
N/A
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