We are looking for a Senior Machine Learning Engineer to develop train optimize and benchmark scientific state-of-the-art deep learning methods for computer vision 3D reconstruction and remote sensing applications including Synthetic Aperture Radar (SAR).
Tasks to be performed:
Data preparation and analysis for real and synthetic training datasets (in particular datasets of SAR data: raw data and focused images)
Collaborate with scientific researchers to design implement test and benchmark deep learning methods.
Collaborate with scientific researchers to analyze the implementation of state-of-the-art methods.
Conduct hyperparameter tuning of the models and optimize the consumption of resources when training the models.
Collaborate with scientific researchers to conduct experimental validation of new methods and benchmarking with respect to state-of-the-art methods.
Required skills experience and candidate profile:
Masters in engineering or another relevant field.
At least 3 years of experience in ML engineering including model development training optimization deployment and evaluation.
At least 3 years of experience in remote sensing and geospatial data domains.
Synthetic Aperture Radar (SAR) data processing and analysis including preprocessing techniques (e.g. radiometric calibration speckle filtering) geometric correction and domain adaptation of ML models for SAR and remote sensing imagery.
Strong Python programming skills with experience in machine learning (ML) frameworks like PyTorch.
Deep understanding of ML especially deep neural network (DNN) architectures and experience with supervised and self-supervised learning.
Experience with version control with Git and containerization with Docker.
Experience with fast prototyping and deployment of DNN models for computer vision tasks.
Additionally we will also value experience in the following areas:
Experience with radiance fields techniques such as Neural Radiance Fields (NERF) and 3D Gaussian Splatting (3DGS) and their adaptation to non-optical modalities like SAR or multimodal data fusion.
Experience leading teams of up to four people in R&D and innovation projects.
PhD in computer science AI ML and/or Robotics and/or Remote Sensing.
At ARQUIMEA we value diversity and inclusion. We do not discriminate on the basis of race color religion gender sexual orientation gender identity national origin age disability or other protected factors by law. All candidates will be considered equally based on their skills and experience
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