
Machine Learning DSP Engineer
Required skills
- Machine Learning
- RF Sensing
- Statistical Signal Processing
- Wireless Systems
- Python
- DSP
- Deep Learning
- PyTorch
- Tensorflow
- open ended problems
Nice to have
- advanced signal processing concepts
- multirate signal processing
- polyphase filterbanks
- TensorRT
- CUDA
- C++
Role summary
DeepSig Inc. is seeking a Full-time Machine Learning DSP Engineer to combine software digital signal processing and software-defined modems with machine learning techniques for AI-Native wireless communications systems. The role involves developing and validating ML and communications system algorithms and software for modem and/or wireless sensing solutions. Responsibilities include building ML models for RF sensing, optimizing training/inference pipelines, and working with real-world RF datasets. Requires an MS/PhD in a related field, proficiency in Python, familiarity with Deep Learning frameworks (PyTorch, Tensorflow), and experience in Deep Learning, RF Sensing, Statistical Signal Processing, Wireless Systems, or Time/Frequency analysis.
Description
Type: Full-Time (W2) On-Site/Hybrid, Arlington, VA
DeepSig Inc. is a venture backed and product centric technology startup building revolutionary wireless processing software solutions using cutting edge machine learning techniques to transform baseband processing, wireless sensing, and other key wireless applications.
We are seeking Full-time Machine Learning DSP Engineer who will help combine elements of software digital signal processing and software-defined modems with state of the art machine learning techniques to create the next generation of AI-Native wireless communications systems in simulation and in real deployed products at scale. This person will be responsible for developing and validating machine learning and communications system algorithms and software across modem and/or wireless sensing system solutions.
What You'll be Doing
- Build cutting edge Machine Learning models for RF sensing applications
- Keep up with the latest developments in the field of Machine Learning and assess their viability for RF sensing applications
- Utilize both Software and DSP techniques to optimize training and inference pipelines
- Work closely with product managers and business development teams to improve our RF sensing capabilities based on customer feedback
- Working with real-world RF datasets and ML driven RF systems which are unique and unrivaled anywhere else in the world
Requirements:
- MS or PhD in Electrical/Computer Engineering, Computer Science, or related field
- Proficient in at least one programming language (Python preferred)
- Familiarity with at least one of the Deep Learning frameworks (e.g. – PyTorch, Tensorflow etc.)
- Experience in one or more of the following areas: Deep Learning, RF Sensing, Statistical Signal Processing, Wireless Systems fundamentals, Time/Frequency analysis of signals
- Ability to work on open ended problems, building candidate solutions and coming up with appropriate metrics for comparison
- Strong communication and teaming skills to work collaboratively and productively in a small company environment
Bonus:
- Experience with advanced signal processing concepts such as multirate signal processing, polyphase filterbanks etc.
- Prior experience in building Deep Learning models for edge deployment
- Familiarity with TensorRT
- Proficiency in C++ and/or CUDA
WORKING AT DEEPSIG
DeepSig is growing its technical team while cultivating a collaborative, agile, and fun small-team culture. We value creativity, knowledge sharing, and employee growth, and we encourage participation in scientific publications, conferences, and open-source software. We offer competitive salaries and benefits, an employee stock option grant program, an environment where we are excited to be transforming and disrupting how signal processing is done with AI/ML, a welcoming and inclusive environment, a flexible schedule, and a great work / life balance.
DeepSig is an equal-opportunity employer and does not discriminate based on race, ethnicity, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability. We are dedicated to cultivating an inclusive, diverse, and engaging workplace where individuals feel fulfilled, inspired, and motivated. We value the unique perspectives that our team brings.
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