Machine learning engineer- UAS navigation

Company Details

Unlocking the value of deployable autonomous technology

We have an exciting role available where you will join our team to solve autonomous navigation in challenging environments without reliable GPS signals to protect lives in military and civilian use cases. You will be working with a team of engineers to develop the hardware and software to allow drones to navigate using visual information. You will be responsible for researching, developing, and deploying novel computer vision algorithms for autonomous navigation. As our work is highly knowledge driven you will spend a lot of time being trained in and pioneering the use of novel deep learning frameworks, cloud computing, and 3D simulation to be able to handle the large volumes of data and deliver world-leading technology to our customers.

Day-to-day tasks you work on might include:

  • Researching, designing, and implementing novel machine learning and computer vision solutions to assist autonomous navigation
  • Exploring the latest and greatest in computer vision algorithms from scientific literature and conference publications
  • Running 3-D Simulations to evaluate and improve performance of visual navigation algorithms
  • Live flight trials, testing of your algorithms and analysing data to make improvement

What do you need to have?

  • Excellent Python coding skills
  • Excellent skills in deep learning (CNN training, testing, evaluation and deployment)
  • Proficient with multiple machine vision / machine learning frameworks (PyTorch , Tensorflow,
  • OpenCV, Kornia, TensorRT, etc.) with a strong portfolio of development examples
  • What would be great to have?

You don’t need these to apply, but if you do, highlight them to help your application stand out:

  • Experience with computer vision tasks like object recognition, semantic segmentation
  • Experience developing AI / ML solutions for robotics platforms using ROS
  • Navigation and positioning/ camera pose estimation algorithms eg. visual odometry, SLAM
  • Experience deploying deep learning models to edge hardware
  • Experience developing scalable machine learning pipelines in the cloud
  • Solid understanding of conventional computer vision techniques
  • Experience with robotics simulation platforms
  • Familiarity with automation and DevOps (Docker, CI/CD)
  • Software development using C++

Other requirements:

  • Location: All hardware and much of the flight-related work is based at the Harwell Science and
  • Innovation Campus. Visits to the office for collaboration are therefore strongly preferred although much of the software development can be done remotely.
  • Security clearance: You will need access to government restricted info to do the work, so you must be willing to and be eligible to pass security checks.

What you’ll get in return:

  • Merit-based compensation (salary, bonuses, shares options scheme)
  • Training & development programs (e.g., drone pilot training)
  • The ability to make a measurable difference in a small company building cutting edge technology with big visions
  • Flexibile work: Options for flexible working hours, working from home (when feasible) and custom arrangements that matter to you
  • A culture of supportive team and high ownership so you can get as much responsibility as you are willing to take on
  • A variety of perks: Gym discounts, cinema half price, free phone insurance, shopping, and supermarket discounts plus many more!

Tagged as: tensorflow, opencv, TensorRT, kornia, Docker, ci/cd, pytorch

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