FULL-TIME PERMANENT POSITION
Terramera is actively seeking a talented senior engineer for our Machine Learning team to drive and support out work in soil carbon analysis.
The successful candidate will contribute to our ambitious projects to promote and enable regenerative agricultural practices, including the development of tools to support farmer and agronomist decision making and methods to quantify soil carbon sequestration.
Reporting to the Machine Learning Manager, the Senior Machine Learning Engineer will work closely with our Robotics, Software Engineering, and Geospatial Information Systems (GIS) teams to help process satellite, drone, and field rover images from massive multispectral datasets and use them to gain insight into soil properties.
Research and develop cutting-edge edge machine learning / deep learning models
Support implementation of analysis pipelines to process large datasets captured by various imaging platforms
Research and help implement algorithms involving active learning, synthetic data, uncertainty modeling, semi-supervised learning to improve sampling and model performance
Collaborate with and receive guidance from our Software, Robotics, and GIS teams to put your models and algorithms into production
Mentor ML team members by providing support and constructive feedback on their work
Support development and maintenance of code with an eye on production
Performs other related duties and tasks as required
M.Sc. or Ph.D. in Engineering, Computer Science, or an equivalent combination of experience and knowledge
5+ years’ experience in applying machine learning and deep learning concepts to real-world problems
Familiarity with deep learning network architectures (e.g., convolution neural networks, recurrent neural networks, single shot detectors) and frameworks (e.
g. Tensorflow, PyTorch, Caffe)
Solid programming skills with a focus on writing clean / maintainable code with experience in Python (preferred), Java, or C++ programming
Experience with putting models into production, including exposure to ML DevOps methods and tools
Strong analytical ability and mathematical skills
Matured communication and critical thinking ability to influence and propose analytics strategies that challenge status quo thinking
Knowledge and experience with the Agile project management methodology
Professional experience applying machine learning techniques in at least one of the following domains : agriculture, remote sensing, satellite imaging, soil science, soil carbon, and / or spectroscopy
Portfolio of completed machine learning projects available for review
Experience with parallel and distributed training of deep learning models
Experience applying machine learning techniques to massive datasets
Exposure to imaging system components (sensors, optics, lighting)
Experience with Bayesian neural networks and / or active learning
Exposure to GIS processing tools (e.g., ArcGIS, Geopandas)
QUALITIES WE’RE LOOKING FOR
Aptitude for interdisciplinary collaboration
Highly conscientious with strong follow-through
Capable of performing research on best practices and communicating results to a non-expert audience
Able to apply domain knowledge to ambiguous and novel situation