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Employer: SynapsE Technology Corporation 

Summary

  • Location: 1043 High Street, Palo Alto (close to Caltrain)
  • Stage: Undisclosed Seed
  • Founded: 2016
  • Investors: This is still private but they are big name VCs & individuals you would know well!
  • Notable Accomplishments:
    • Partnered with worlds 2nd largest  X-ray and security company
    • They're actively having conversations and advised by experienced members of the TSA as well as the largest airports in international destinations like Japan and France
      Company Size: 5
  • Engineering Size: 2
  • Tech Stack: Python, C/C++, Golang, Docker, AWS, Django, Flask, Tensorflow, PyTorch, Caffe
  • Visa: No
  • Remote: No.
  • Travel: The Full Stack Engineer is required to travel onsite and work at client locations periodically
  • Additional Links:
  • Compensation: (DO NOT SHARE WITH CANDIDATE)
    • Computer Vision and Infrastructure: $100K – $180K, 0.1% – 1.5%
    • Fullstack: $100K – $170K, 0.1% – 1.2%
  • Interview Process:
    1. ~30 min call with CEO, Bruno
      • Topics include: ~10min about the company, ~15min for the candidate to explain their work and accomplishments relevant to the role, Any remaining time to talk about relevant systems experience or research paper knowledge for the Computer Vision role, plus questions.
    2. ~45 - 60min call with CTO, Simanta (Goes by Sims)
      • Case -by-case basis for Computer Vision only, there's a Homework assignment which can take between 2 - 4 hours
      • Topics include: Diving into field specific knowledge, discussing highly technical engineering challenges relevant to their field of work (Large scale, system redundancy, complex Algorithms for the CV role, etc). 
        • Choose a model
        • Explain challenges implementing the model
        • Talk about your experience and relevant interest to their team/role 
    3. ~4 hour onsite (order varies) 
      • 1 hour with CTO, Simanta (Goes by Sims)
      • 30 min with President, Ian OR CEO, Bruno
      • 1 hour with Principal Engineer, Gordon
      • 30 - 60min with team for Lunch
        • Topics include: more of the same from step 2 as well as diving deeper into what personally motivates the candidate.

Quick Pitch:

Synapse is a deep learning and computer vision software system which automates threat detection in the security & defense space through visual analysis. Their technology reaches into automated highly accurate airport scanners, building security, and more!

Company Overview

Synapse Technology Corporation modernizes the defense image intelligence industry with proprietary deep learning and computer vision technology. Synapse Technology first tackles security screening checkpoints with our intelligent threat detection system, which operates on baggage X-Ray & CT scanners. As a member of the US Government OTAP program, we are collaborating with TSA, Sandia National Labs, and checkpoint OEMs. Current baggage security checkpoints have a low accuracy due to their dependence on inaccurate human perception to identify prohibited items. Our software systems increase accuracy significantly, while helping operators avoid false positives with our safe-item detection ability.

Position 1: Computer Vision and Machine Learning

Must Have

  • 3+ years of hands-on experience with applied computer vision and machine learning algorithms, in a research lab or company environment.
    • College experience is fine but needs to be SUPER deep into very detailed research papers and CV knowledge/algorithms.
  • Publications or significant projects undertaken in machine learning.
  • Programming experience — Comfortable with large projects in Python or C++, and excellent software engineering skills. Good habits around testing, documentation, and writing robust and maintainable code.
  • Solid mathematics background (linear algebra, 3D geometry, probability, optimization).
  • Expert knowledge in deep learning architectures for computer vision, and associated libraries & frameworks (Tensorflow, PyTorch, Caffe).

Responsibility

  • Working with 2D and 3D datasets from various sensors (x-ray, CT, LIDAR, etc.) to develop generative and discriminative models.
  • Training and deploying machine learning models for object detection, tracking, and recognition.
  • Adapting deep learning methods with traditional computer vision methods to build robust, configurable systems.

NOT Looking for

  • Deep learning NLP (Natural language processing).

Position 2: Infrastructure Engineer

Must Have

  • Minimum 5 years experience as a Software Engineer.
  • Past work building Linux or Windows server systems.
  • Working knowledge of Docker or other virtualization tools.
  • Experience with AWS or other IaaS platforms.
  • Comfortable with Go, C, or C++ on the backend.
  • Past work on systems that handle data securely, both in storage and transmission (e.g. health or financial data).
  • Past work in designing and building large systems.

Nice to have

  • Contributions to open source projects.
  • Experience developing supporting infrastructure for machine learning.
  • Experience with diverse systems and architectures.

Position 3: Full Stack Engineer

IMPORTANT: This role will involve periodic travel to domestic and international client sites. Travel may arise when scoping out potential client or partner architectures or in the final steps of integrating and testing a deployment.
Must Have

  • Minimum 2 years experience as a Software Engineer.
  • Proficient knowledge in Python, Go, or another back-end language.
  • Experience with server frameworks (such as Django, Flask).
  • Solid understanding of UI design in both web and desktop environments.
  • Experience with AWS or other IaaS platforms.
  • Strong theoretical and practical knowledge of security principles in deployed applications.

Nice to have

  • Contributions to open source projects
  • Previous enterprise-grade projects

 

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