AI-Native Wireless ML DSP Engineer (RF Sensing)

Socket.dev; Arlington (VA); Hybrid; USD 120,000 - 190,000; Full time

Job summary

DeepSig Inc. in Arlington, VA seeks a Full-time Machine Learning DSP Engineer for on-site/hybrid work. You will develop ML models for RF sensing, combining software DSP and ML techniques to improve wireless systems.

You will work with real datasets and collaborate across product teams. Required are an MS/PhD in a related field, Python, and experience with PyTorch or TensorFlow, plus knowledge of C++/CUDA and TensorRT for deployment.

Qualifications

• MS or PhD in Electrical/Computer Engineering, Computer Science, or related field.
• Strong programming skills in Python; experience with ML frameworks.
• Background in deep learning and RF sensing related topics.
• Knowledge of wireless systems fundamentals and signal analysis.
• Ability to design and evaluate ML/communication algorithms.

Responsibilities

• Build cutting edge Machine Learning models for RF sensing applications.
• Keep up with the latest developments in ML for RF sensing and assess viability.
• Optimize training and inference pipelines using software and DSP techniques.
• Collaborate with product managers and business teams to incorporate feedback.
• Work with real-world RF datasets and ML-driven RF systems at scale.

Skills

Python programming

Deep learning

Statistical signal processing

Wireless communications fundamentals

Time/Frequency analysis

Education

MS/PhD in Electrical/Computer Engineering or CS

Tools

PyTorch

TensorFlow

TensorRT

C++

CUDA

Job description

DeepSig Inc. in Arlington, VA seeks a Full-time Machine Learning DSP Engineer for on-site/hybrid work. You will develop ML models for RF sensing, combining software DSP and ML techniques to improve wireless systems.

You will work with real datasets and collaborate across product teams. Required are an MS/PhD in a related field, Python, and experience with PyTorch or TensorFlow, plus knowledge of C++/CUDA and TensorRT for deployment.