TurbineOne

👥 11-50💰 $15,000,000 Series A about 1 year agoSecurityPublic Safety💼 Private Company
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TurbineOne is a company focused on innovative product engineering solutions, currently seeking to expand its team with Senior and Principal level engineers.

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🔍 DefenseTech

  • 8+ Years working in Product Engineering or Front End Client development positions.
  • Reactive framework experience (Vue, React, Unity etc)
  • Experience with API design and best practices for REST and GraphQL
  • You have demonstrable experience working through ambiguity, navigating uncertain product domains, or becoming involved cross functionally.
  • You’ve been involved in technical design review processes, review boards, or similar thoughtful exercises on technical design considerations.
  • Deliver product experiences built on the T1 Artificial Intelligence and Networking platforms, serving the needs of Intelligence and Security staff around the world.
  • Collaborate with Design and Product Management on feature design, delivery schedule and trade off decision points.
  • Be a product owner - there are no tickets to crunch here, be an active builder and designer, shaping the direction of T1’s code and features.
  • Build and innovate on our front end architecture and design system which is a Vue 3 client on a Golang server, with a MongoDB storage layer
Posted 8 days ago
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🔍 DefenseTech

  • 7+ years of full stack work experience
  • Experience in a production software development environment (version control, automated testing, build tools)
  • Knowledge of deep learning algorithm development and experience with ML experimentation
  • Experience with all or some of TensorFlow, PyTorch and Jax.
  • Designing and developing machine learning systems and infrastructure for training and inference at the edge
  • Maintain and update the APIs between products and ML features to enable rapid iteration and adoption of new functionality
  • Shipping production grade machine learning features to TurbineOne’s Front Line Perception system
  • Building and integrating new data models and user interfaces for gathering user data to enable to new ML-based product solutions
  • Creating and maintaining reusable functional blocks for machine learning models, such as data loading, inference batching, etc.
  • Productionizing machine learning prototypes, papers and state-of-the-art architectures to solve product problems
  • Maintain and improve existing TurbineOne machine learning frameworks and libraries
  • Developing automation tools for building, testing, packaging and deploying machine learning components and features
Posted 5 months ago
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