Machine Learning Engineer
Tasks
- Analyze RF datasets and develop predictive models
- Benchmark performance and improve deployed models
- Define machine learning use cases with cross functional teams
- Design data pipelines for training testing and validation
- Develop software prototypes and integrate ML with radio firmware
- Research and implement machine learning algorithms for wireless communication
- Stay current with machine learning research for wireless and embedded systems
Perks/Benefits
- Background check clearance
- Drug Test Clearance
- Hybrid schedule
- Onsite days Mondays Wednesdays Thursdays
Skills/Tech-stack
3GPP | Adaptive modulation | Anomaly Detection | Beamforming | C# | C++ | Cognitive radio | DSP | DSP algorithms | Edge Computing | Embedded Machine Learning | GPU Acceleration | IEEE 802.11 | MATLAB | MIMO | Machine Learning | Model Optimization | OFDM | PyTorch | Python | RF signal classification | Real Time | Real-time Systems | Scikit-learn | Signal Classification | Signal Processing | Spectrum sensing | Statistical modeling | Supervised Learning | TensorFlow | Time Systems | Unsupervised Learning | Wireless Communications
Education
Regions
Countries
States
Cities
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