Join Our Team

VP Software Development

DESCRIPTION

We are seeking a Vice President of Software Development & Machine Learning Engineering who will manage the global software engineering team, collaborate with product managers/business customers, support the company’s product vision, and lead the development of our AI/Machine Learning strategy. You will be responsible for product delivery balancing the three give-take tradeoffs of software engineering: time/budget, quality, and features.

The key responsibilities include software development hiring/performance management, defining key metrics, supporting scrum/resource-assignments, and ensuring software development productivity. The criteria for success for this role include on-time product delivery, system uptime, software robustness/uptime, and quality assurance.

RESPONSIBILITIES

  • Lead the global software development team: Cloud-software engineers, firmware engineers (both full-time engineers and contractors)
  • Key stack capabilities: Python, MySQL/Postgres/Snowflake, Google Cloud/AWS, Tensorflow/Pytorch, Google Coral AI
  • Oversee Artificial Intelligence and Machine Learning technology: data pipelines and workflows
  • Own the KPI’s for the performance of our services that tie the technology to business outcomes:
  • Availability/Uptime
  • Response times (internal guard-facing, consumer-facing, & partner-facing)
  • Capacity & costs
  • AI Precision/Recall
  • Manage developers across various skills: Software development, ML/AI, Devops, QA

LEADERSHIP REQUIREMENTS

  • 10+ years of hands-on technology leadership experience. Must have experience in at-scale (100k’s of customers, High-speed, low-latency, high-availability) cloud-services spanning application-level, dev-ops and operations level. Must have 5+ years of experience managing global development teams.
  • 5+ years working with AI/ML engineers to develop real in-world applications (i.e., customer-facing applications, not research or back-end processes)
  • Familiar with Zero-Trust security environments, 2FA, and other key cybersecurity practices
  • Analytically driven; leverages analysis and metrics to drive decisions
  • Big Pluses: Experience with streaming video, Experience with hardware/firmware

STARTUP (CULTURAL FIT) REQUIREMENTS

  • High on emotional intelligence with a talent for building great teams, especially at passion-driven early-stage companies and helping them scale with a sprinkle of process, structure and tooling
  • Entrepreneurial – a fast thinker and problem solver; hard charging, but thoughtful; willing to take risks.
  • Driven to win. Can thrive in a dynamic environment, yet is seen as a deep keel amid the chaos.
  • Doesn’t take self too seriously; has a good sense of humor.

Machine Learning Engineer

DESCRIPTION

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.

RESPONSIBILITIES

  • 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.

QUALIFICATIONS

  • 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.)