Company Description
Omni Instrument is an early-stage startup for the manufacturing industry. We build autonomous manufacturing tools using Edge devices, custom hardware for perception and controls. We are looking to grow our team to accelerate our product development for our customers.
Role Description
As a Founding Computer Vision Engineer, you will own hardware and software for edge devices and leverage latest GPUs via cloud computing for creating the SOTA models for perception. You will work closely with Mechanical, Electrical and Software Engineers to blend in the product requirements for our customers. We are looking for great collaborators with good engineering discipline who are passionate about Robotics.
This is an on-site role in San Francisco, CA and you will report directly to the CEO.
You will:
· Select the optimal sensors needed to produce the most robust solution.
· Work hands on NVIDIA Jetsons and GPUs to create the best models for deployment.
· Integrate existing open-source models or custom models on NVIDIA Jetsons.
· Perform various sensor calibrations and setup hardware periodically.
· Design experiments and validate exiting algorithms into production.
· Analyze test data, communicate the results in technical reports and presentations.
You have:
· An advanced degree in Computer Science, Robotics, Engineering or other relevant technical field.
· Domain level expertise in at least one or more Computer Vision, SLAM, Deep Learning, and Control Systems.
· Experience in Software Engineering and willing to work with Hardware.
· Modern C++ (17/20), Python.
· Comfortable juggling multiple responsibilities across software and hardware.
· Comfortable with Machine Learning Libraries such as PyTorch and TensorFlow.
· Good understanding of ROS/ROS 2 and DDS.
· Experience managing projects with multiple contributors and stakeholders.
We Prefer:
· Publication in CVPR, ECCV, IROS, ICRA, and other conferences.
· Open-source developers and hackers with solid GitHub portfolio.
· Expertise in Sensor Fusion such as Kalman Filters, Particle Filters etc.
· Deployed Neural Networks on Edge Devices using TensorRT and safety critical systems.
