Field Application Engineer (Machine Learning)

Posted 18 Days Ago
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Seoul
Mid level
Hardware • Machine Learning • Software
The Role
The Field Application Engineer supports customers by installing SDKs, analyzing systems, conducting training, and troubleshooting with engineering teams to resolve issues related to neural processing units.
Summary Generated by Built In

Description

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 Field Application Engineer (FAE) will work closely with Business Development, Product, and Engineering to provide pre-and post-sales technical customer support. This position requires excellent customer communication and troubleshooting skills to conduct remote and on-site training and product presentations. This position is a technical position that will require additional skills such as system debugging, coding, scripting. Candidates are expected to work independently and acquire expert-level skills with the in-house built product line including HPC Hardware (IP, Chips, Boards), SDK, Algorithms (NN, DSP, Vision, Path Planning, etc.).

Responsibilities:

  • Work with Business Development to sell the technology from quadric.io
  • Work with customers to install SDK and algorithms and analyze customer systems to determine the best HW/SW solutions for their system.
  • Analyze technological problems brought in by customers and communicate with engineering for the best solution..
  • Work with business development to prepare technical proposals and statements of work, working with the customer to gather requirements.
  • Set up regular technical discussions with customers to help them understand quadric deliverables and resolving customer issues with engineering support as well as conduct regular follow-up and monitoring.
  • Deliver periodic training sessions
  • Coordinate with the Sales and Engineering team in designing proper application systems and formulating the product specifications according to the customer's needs.
  • Interface with product marketing and engineering
  • Conduct project feasibility studies
  • Some travel required
Requirements
  • Bachelor’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.
  • Fluent in Japanese & English.
  • 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 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)
  • Paid Time Off (Vacation, Sick & Public Holidays)
  • Family Leave (Maternity, Paternity)
  • Training & Development
  • Work From Home
  • Stock Option Plan

Top Skills

Docker
Linux
Onnx
Python
PyTorch
TensorFlow
Tensorflow-Lite
Unix
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The Company
HQ: Burlingame, CA
38 Employees
On-site Workplace
Year Founded: 2017

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.

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