Remote Sensing – Deep Learning Engineer – Point Clouds

Application closes Friday, 29 September 2023

The Company: 

 Interpine is committed to “shaping today’s forest with the technology of tomorrow”. Our focus on research and innovation sets us apart from other industry providers, as we continue development of step change technology in the forestry sector. We are a committed team of professional foresters, qualified technicians, data analysts, UAV operators and field workers that provides cutting edge solutions across the sector.

About the role:

This role will be based with our Remote Sensing team in Rotorua. The main focus will be working with ultra-dense LiDAR data to extract and measure 3D tree profiles, using techniques including deep learning and virtual reality.    

We’re looking for a DL Engineer with experience working on LiDAR based point cloud data for object detection and classification and tracking. You’ll need a firm understanding of point-cloud technology and you’ll need to know your way around ML frameworks like Tensorflow, Pytorch, or similar. 

This is a great opportunity to gain valuable experience working with skilled remote sensing and forestry professionals, and to get an insight on how an effective team operates in an environment that interests you. 

The pay range will be $70,000 – $100,000 depending on experience. The working week is 40 hours with the possibility of occasional overtime by mutual agreement. 

What you’ll bring:

  • Training state-of-the-art Deep Neural Networks for mapping & localization.
  • Taking DNNs and algorithms from initial evaluation and experimentation all the way to an operational product.
  • Defining and collecting training datasets.
  • Working with a variety of sensors: cameras, LiDAR, radar, GPS.
  • Building training pipelines (PyTorch, TensorFlow, TensorRT, Python, C++).

What We Need To See 

  • MSc or PhD in Computer Science, Applied Mathematics, Robotics, or equivalent experience.
  • Someone who is passionate about Artificial Intelligence. 
  • Ability to learn new things and enjoy solving difficult problems.
  • A high level of mathematic knowledge.
  • Strong experience in Deep Learning / Machine Learning and a background in computer vision.
  • Advanced programming and debugging skills in C++ and/or Python.
  • Good communication and analytical skills. Ability to work with multiple teams in a dynamic environment.
  • In case you are still a student, you will need a support letter from your supervisor with the title of your final project and the expected time of completion.

Ways To Stand Out From The Crowd 

  • Proven background in applying Deep Learning to 3D Computer Vision problems.
  • Experience with Unsupervised or Self-supervised Learning.
  • Experience fusing data from different sensor modalities (e.g. Images and LiDAR data) to enable information conflation, label propagation and cross training.
  • Background in developing real-time LiDAR and/or Computer Vision systems.
  • Good understanding of remote sensing techniques and applications.

What we can offer you:

  • Experience working with cutting edge technology in an industry leading company. 
  • A variety of work, from computer programming to LiDAR analysis. 
  • Great office environment and location, based in Rotorua and within walking distance to Rotorua’s famous Redwoods walking and mountain biking tracks.

The Location:Rotorua

The Rotorua lakes with surrounding bush and mountains means Rotorua is hard to beat for an outdoor lifestyle. Boating, mountain biking, tramping, hunting and fishing are all on the doorsteps of a beautiful city with affordable housing. Rotorua’s central location means most of the North Island is within easy driving reach. 

How to apply:

Your application should include a cover letter and CV which includes the details of contactable referees.  CVs which say “referees available on request” won’t be considered as the referee details are being requested as part of the application process in order to verify work experience.  Short listed candidates will also be asked to provide evidence of their qualifications.

Applications should be emailed to:

The successful applicant will be required to undergo pre-employment screening and a drug test.