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Machine Learning DSP Engineer

DeepSig Inc
Posted 22 days ago, valid for 13 days
Location

Arlington, VA, US

Salary

Competitive

Contract type

Full Time

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Sonic Summary

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  • DeepSig Inc. is seeking a Full-time Machine Learning DSP Engineer to develop and validate machine learning and communications system algorithms in Arlington, VA.
  • Candidates should have an MS or PhD in Electrical/Computer Engineering, Computer Science, or a related field, along with experience in areas like Deep Learning and RF Sensing.
  • The position involves building cutting-edge Machine Learning models for RF sensing applications and requires proficiency in at least one programming language, preferably Python.
  • DeepSig offers competitive salaries, benefits, and an employee stock option grant program, although the specific salary is not mentioned in the job description.
  • The company promotes a collaborative culture and values creativity, knowledge sharing, and employee growth, making it an inclusive environment for all team members.

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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