At FortressIQ we’re building cutting-edge process cognition technology to improve people’s work lives, by helping automate routine tasks, and allowing them to focus on higher value work and more meaningful interactions. Based on the latest advancements in computer vision and machine learning, we’re delivering the tools businesses need to quickly and effectively empower the digital workforce on an enterprise scale.
We’ve built the first AI platform that can understand a company’s workflows through simple observation, radically improving their organizational understanding. Our work encompasses the fields of enterprise software, cloud computing, computer vision, automation and AI—if you’re interested in defining and building the future of large-scale enterprise business tools, join us.
The ideal candidate will be primarily involved in the research, design and implementation of deep learning solutions that are critical to our company’s success. These projects will span multiple domains applicable to deep learning including, but not limited to, both image and text analysis.
This is the perfect opportunity to join an innovative and energetic team that develops analysis tools which will influence both our products and clients.
Who You Are
- 5+ years of experience in deep learning, specifically in areas of Bayesian networks, Probabilistic graphical models, Generative Adversarial Networks (GANs), Markov Decision Process (partial observability or POMDP, learning automata and Q-learning), Deep Convolutional Neural Nets, RNN/LSTM
- Experience with driving high level algorithm decisions ensuring fast and accurate machine learning in different applications
- Experience with implementing object classification and detection making use of cutting-edge deep learning techniques for computer vision such as Faster-RCNN, Mask-RCNN, and edge AI (MobileNet, SqueezeNet, YOLO)
- Experience with ML frameworks such as Tensorflow or Pytorch
- Master's or PhD in Computer Science, Statistics, Applied Math, AI or related field
- Excited to experiment with new technologies and approaches
- Enjoy collaboration and success in small, high-velocity teams
- Excellent problem solving and debugging skills
- Attention to detail, bordering on obsessive
- A desire to automate everything
- Experience in Anomaly and Cycle detection
- Experience with OpenCV, Tensorflow Serving, Docker and/or Kubernetes
- Have a strong academic background with prominent research that’s been recognized at leading conferences and journals. (CVPR, ECCV, ICCV, ICML, NIPS)