Hybrid AI-Native Wireless DSP Engineer

DeepSig Inc; Arlington (VA); Hybrid; USD 120,000 - 190,000; Full time

Benefits offered by this job

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Job summary

DeepSig Inc. in Arlington, VA, is seeking a Full-time Machine Learning DSP Engineer to combine software DSP and ML for AI-native wireless systems. You will develop and validate ML and communications algorithms across modems and sensing systems in simulation and deployed products.

Requirements include MS/PhD in Electrical/CS, Python proficiency, and experience with DL frameworks such as PyTorch or TensorFlow. Bonus: TensorRT, CUDA, and C++.

Qualifications

• MS or PhD in Electrical/Computer Engineering, Computer Science, or related field.
• Proficient in Python (preferred).
• Experience with Deep Learning frameworks (PyTorch, TensorFlow, etc.).
• Experience in Deep Learning, RF Sensing, Signal Processing, and Wireless Systems fundamentals.

Responsibilities

• Build cutting edge Machine Learning models for RF sensing applications.
• Keep up with latest ML developments and assess viability for RF sensing.
• Utilize Software and DSP techniques to optimize training and inference pipelines.
• Collaborate with product managers to improve RF sensing capabilities based on customer feedback.
• Work with real-world RF datasets and ML-driven RF systems.

Skills

Python

Deep Learning

PyTorch

TensorFlow

Machine Learning

Signal Processing

Education

MS/PhD in Electrical/Computer Engineering or CS

Tools

TensorRT

CUDA

C++

Job description

DeepSig Inc. in Arlington, VA, is seeking a Full-time Machine Learning DSP Engineer to combine software DSP and ML for AI-native wireless systems. You will develop and validate ML and communications algorithms across modems and sensing systems in simulation and deployed products.

Requirements include MS/PhD in Electrical/CS, Python proficiency, and experience with DL frameworks such as PyTorch or TensorFlow. Bonus: TensorRT, CUDA, and C++.