Applied ML Engineer
Tasks
- Build real time sensor processing pipelines
- Design, train, and evaluate machine learning models
- Develop benchmarking data visualization and debugging tools
- Develop dataset labeling strategy
- Evaluate new research and tools for product roadmap
- Implement data augmentation and synthetic data generation
- Monitor model performance and tune model behavior
- Optimize model architectures and inference pipelines
- Perform code reviews and maintain technical documentation
- Support model prototyping and experimentation
Perks/Benefits
Skills/Tech-stack
Anomaly Detection | Computer Vision | Cross-validation | Data Augmentation | Domain Adaptation | Edge Computing | Embedded Machine Learning | Hardware-Aware Optimization | Hyperparameter Tuning | Image classification | Machine Learning | Model Compression | Model Monitoring | Multimodal fusion | Object Detection | PyTorch | Python | Sensor fusion | Signal Processing | Synthetic data | TensorFlow | Time Series
Education
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