Job Type
Full-time
Description
Company Overview: DeepSig Inc. is a venture-backed technology company pioneering the use of AI in 5G and other wireless systems by replacing traditional signal processing with machine learning. DeepSig software products achieve significant performance increases while reducing power consumption to bring value to our customers.
Job Summary: We are seeking a full-time Embedded Software Engineer who will be an integral part of our growing team as DeepSig further deploys its AI/ML 5G/6G products into embedded devices. The role will work in the areas of algorithm optimization, embedded systems, accelerators, machine learning and wireless communications. The ideal candidate will have a proven track record of implementing wireless algorithms on an embedded device utilizing various SIMD, DSP, NN, or other accelerators.
Some of What You'll be Doing:
Design, develop, and optimize AI/ML and DSP algorithms for 5G Physical Layer
Work with and integrate our software within Open RAN stacks such as Qualcomm L1, Nvidia Aerial, and Intel FlexRAN
Collaborate with the ML team to ensure solutions can be effectively and efficiently implemented on embedded platforms to take advantage of on chip accelerators (SIMD, DSP, NN)
Work with the rest of the 5G team to propose conventional DSP solutions to augment and improve our existing capabilities.
Implement algorithms using mixed precision to achieve high accuracy and low latency requirements
Work with DeepSig RAN engineers to deploy and validate DeepSig's 5G capabilities
What We Need to See:
7+ years of experience in the required skills
Experience with development, debug, and simulation for an embedded platform
Programming skills in C, C++, or Python
Experience with fixed and mixed precision algorithms
Development in 5G NR and LTE physical layer.
Proven experience utilizing on board accelerators such as SIMD, DSP cores, NPU cores, or FPGAs
Ability to work in a flexible, fast-paced, and dynamic startup environment.
Proficiency with modern software development practices such as version control, continuous integration, and testing
What We Would Like to See:
Experience using Qualcomm QRU100 and X100 SoC
In-depth knowledge of information theory, coding theory, adaptive filtering, channel estimation, beamforming, and digital communications.
Exposure to AI/ML libraries such as PyTorch and TensorFlow
ML model inferencing with low latency requirements