Quadric has created an innovative general purpose neural processing unit (GPNPU) architecture. Quadric's co-optimized software and hardware is targeted to run neural network (NN) inference workloads in a wide variety of edge and endpoint devices, ranging from battery operated smart-sensor systems to high-performance automotive or autonomous vehicle systems. Unlike other NPUs or neural network accelerators in the industry today that can only accelerate a portion of a machine learning graph, the Quadric GPNPU executes both NN graph code and conventional C++ DSP and control code.
Role:The Corporate Applications Engineer is the key bridge between development engineering and hands-on users in the field. The CAE will [1] lead technical customer support initiatives in collaboration with field application engineers, Business Development, Product, and Engineering teams; and [2] develop supporting applications materials to support the use of Quadric product. This position requires exceptional technical depth, strong coding capabilities, and advanced troubleshooting skills to develop customer demos, benchmarks, and reference implementations using Quadric's SDK. This senior technical role demands expertise in system architecture, algorithm optimization, and the ability to provide technical leadership across global FAE teams. Candidates must demonstrate deep technical mastery of Quadric's product ecosystem including HPC Hardware (IP, Chips, Boards), SDK, and various algorithms (NN, DSP, Vision, Path Planning, etc.).
Responsibilities:- Develop reference implementations, demos, and benchmarks using Quadric's SDK to showcase product capabilities and performance
- Provide technical leadership and support to field application engineers worldwide
- Design and implement optimization strategies for customer applications on Quadric's platform
- Work with Business Development to articulate technical value propositions to potential customers
- Analyze complex customer technical requirements and architect optimal solutions leveraging Quadric's technology
- Create detailed technical documentation, application notes, and implementation guides
- Develop and deliver advanced technical training for customers and internal teams
- Collaborate with Product and Engineering teams to influence product roadmap based on customer needs
- Troubleshoot complex system-level issues and develop solutions in collaboration with Engineering
- Stay current with industry trends, competitive technologies, and emerging applications
- Occasional travel required to customer sites
Requirements
- Bachelor’s or Master's in computer science and/or Electronics Engineering field.
- Minimum 3+ years experience working with customers/business development supporting SDKs.
- Must be able to demonstrate basic knowledge of software perception systems, and/or Computer Vision.
- Proficiency in Python.
- Experience describing, building, running and deploying Docker containers.
- Experience with Linux or Unix based operating systems.
- Experience with at least one of the following neural network / machine learning frameworks: PyTorch, Tensorflow, Tensorflow-Lite.
- Experience quantizing, running and debugging neural networks with PyTorch/ONNX runtime a plus.
- Experience supporting parallel C / C++ languages a plus (CUDA, OpenVX, NEON, etc.)
- Solid understanding of intermediate git concepts such as branching, rebasing, merge conflict resolution, etc.
- Ability to methodically debug problems, relay information to the engineering team, and test and deploy system updates and upgrades.
Benefits
- Health Care Plan (Medical, Dental & Vision)
- Retirement Plan (401k, IRA)
- Life Insurance (Basic, Voluntary & AD&D)
- Paid Time Off (Vacation, Sick & Public Holidays)
- Family Leave (Maternity, Paternity)
- Short Term & Long Term Disability
- Training & Development
- Work From Home
- Free Food & Snacks
- Stock Option Plan
Top Skills
What We Do
Quadric has built a unified hardware/software architecture optimized for on-device machine learning inference. Only the Quadric GPNPU (general purpose neural processing unit) delivers high ML inference performance while also running C++ code without forcing the developer to artificially partition application code between two or three different kinds of processors. Quadric's GPNPU is a licensable processor IP core that scales from 1 to 64 TOPs and seamlessly intermixes scalar, vector and matrix code.
