Machine Learning Engineer

Company: Doxel Inc.
Location: Valley
Posted on: February 20, 2021

Job Description:

In the $12T construction industry, 98% of projects are delivered, on average, 80% over budget. Doxel is on a mission to stop that from happening. Root cause? Inability to measure site progress in an objective, trustworthy and frequent manner. Construction managers are frequently surprised to discover that their multi-million dollar projects have been running behind for several weeks or months. By that point, the money has already been spent and it's too late to fix the problem. Solution Doxel uses robots to survey sites every day, proprietary deep learning and AI based algorithms to assess progress and turns the terabytes of data it collects into simple insights for project managers that enable them to react to issues in minutes, not months. This enables them to constantly correct site inefficiencies and has demonstrated RoI of eliminating overages entirely and even delivering projects up to 11% below budget. Doxel has taken the market by storm since it's launch last year - closing deals with marquee customers such as Kaiser Permanente, Sutter Health and the Lucas Museum of Narrative Art. Team Doxel's team consists of some of the brightest minds in Silicon Valley that include PhDs, engineers, business leaders and civil engineering professionals on the Forbes 30 Under 30 list, graduates from Stanford University and with experience at organizations such as Google Advanced Technologies & Projects. Doxel is backed by Andreessen Horowitz - famed investor that also backed Facebook, Coinbase, Slack, Airbnb, Github and Lyft. The Role Doxel has a distributed infrastructure to capture physical data via LIDAR scanners. You are an expert in 3D or 2D perception algorithms and can turn all of this raw data into insights. You know how complex the real-world can be and know the value of good data collection, labeling, and iterative training/experimentation. You also follow the state-of-the-art papers and can quickly implement proof-of-concepts in just a few weeks. And you don't stop there - you are impact focust and make your models reliable enough (95%+ precision) for production use. You achieve all of this by having the right level of breadth and communication/teamwork skills to move quickly in a startup. Responsibilities

• Training and deploying models that automate our computer vision and robotics problems
• Working on object recognition from 3D point clouds & 2D panorama images, registration and alignment automation
• Work closely with our Data Insights and Computer Vision engineers to deliver accurate, reliable alerts whenever something is misinstalled on $100M+ construction projects - fully automatically.
• Use cutting-edge CV deep learning techniques to solve the aforementioned challenges Minimum Qualifications
  • Master's degree in Computer Science or equivalent work experience
  • 2+ years of experience working with TensorFlow, PyTorch, or other mainstream deep learning framework
  • Expertise in at least one of: C++, Python, Java, Go (two or more preferred)
  • 1+ years of experience with deep learning on production-grade systems at scale. Familiarity with optimization of neural networks for deployment
  • Excellent interpersonal, leadership and communication skills, including the ability to explain complex technical concepts in simple terms and desire to work closely with end-users. Preferred Qualifications
    • Computer vision experience, ideally with 3D point clouds from LIDAR
    • Contributions to research communities and/or efforts, including publishing papers in machine learning venues (e.g: JMLR, ICLR, NIPS, ICML, ACL and CVPR)
    • Experience with cloud development and Google Cloud Platform hosted ML tools Doxel is an equal opportunity employer and actively seeks diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Keywords: Doxel Inc., Columbus , Machine Learning Engineer, Engineering , Valley, Georgia