Machine Learning Engineer
Tasks
- Analyze radio frequency datasets and develop predictive models
- Define machine learning use cases and evaluate deployed model impact
- Design data pipelines for training testing and validation
- Develop software prototypes and integrate ML algorithms with radio firmware
- Perform performance benchmarking and iterative model improvement
- Research design and implement machine learning algorithms for wireless communication systems
- Stay current with machine learning research for wireless and embedded systems
Perks/Benefits
- 401k with company match
- Employee stock purchase plan
- Hybrid schedule
- Medical, dental, vision benefits
- Paid Holidays
- Paid parental and family leave
- Paid time off
Skills/Tech-stack
3GPP | 802 11 | Adaptive modulation | Anomaly Detection | Beamforming | C++ | Cognitive radio | DSP | Data Pipelines | Edge Devices | Embedded Machine Learning | GPU Acceleration | IEEE 802 11 | IEEE 802 15 | Interference mitigation | Link adaptation | MATLAB | MIMO | Machine Learning | Machine learning model optimization | Model Optimization | OFDM | PyTorch | Python | Real Time | Real-time Systems | SDR | Scikit-learn | Signal Processing | Spectrum sensing | Statistical modeling | Supervised Learning | TensorFlow | Time Systems | Unsupervised Learning | Wireless Communications
Education
Regions
Countries
States
Cities
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