Join Our Team

Machine Learning Engineer


We are seeking an experienced machine learning/data science engineer (5+ years in industry experience) to join our small team in building a truly next-generation home security system utilizing all the killer bells and whistles: deep learning, hybrid-cloud, big data, etc.

The right candidate loves data and revels in powerful insights at every step of the machine learning discovery and deployment process–from model analysis, to model design and optimization to real-time model deployment.


  • Develop vision models: We are constantly improving our internal CNN-based models. We use transfer-learning as well as from-scratch training on custom CNN, VGG-like, Inception-like and Resnet-like models.
  • Develop back-end optimization models: We optimize more than camera ML–we measure and optimize the whole workflow behind the cameras–guard performance, event routing.
  • Develop novel training techniques: Supervised, semi-supervised, unsupervised and RL approaches are all part of our toolkit.
  • Optimizing internal DL infrastructure: Managing internal data pipeline including defining data capture, data stores, training clusters, data QC, model QC, performance optimization.
  • Measuring/improving models: We keep an ongoing scorecard of the performance of specific models, the parameters (including training specifics) of that model and the various thoughts/insights from that round of training.


  • Data Science GSD (GET STUFF DONE!): Data science is first and foremost about getting it done–doing the right thing be it data movement, data cleansing, modeling or optimizing.
  • Machine Learning Experience (5+ years total, 2+ years at a commercial enterprise for a production product): This is not an entry-level position for new grads or recent-graduate level students. Whether it’s for search or for NLP or bayes networks or recommender systems, commercial experience with ML-driven systems is a requirement.
  • Experience with massive data sets (10+ TB, image data sets preferred): Experience working with and managing multi-terabyte-dataset sizes is important: Filesystem organization, data pipelines, etc..
  • The Start-Up mentality: The right candidate considers herself/himself to be a “get-’er-done” type of person and is looking to have a huge impact at a small company. Hard work is a must, so the right person exudes positive life-giving energy from solving hard problems, working hands-on and doing things other people consider impossible. We’re going to keep the team super small for the time being (lean startup mode FTW) so you’ve gotta be willing to roll up your sleeves and do everything from writing code to helping out with product and software QA. (PS Good news–the whole team will be like this too, and that’s the best type of team to be on.)