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Revalue Nature: Revalue Nature's mission is to make ecosystems function, at scale. We do this by developing the highest integrity nature-based projects globally, with our team of carbon experts, advanced climate tech and data intelligence platform.
We are building on strong foundations to deliver at scale and with the highest integrity:
What are we looking for?
We are not just another company in this space, we want to be the leaders, and we are rapidly scaling up our team to achieve it. We are looking for the most mission-driven, talented people to grow and scale our impact. If you have a bias towards action and you are driven by our same values and mission, we want to know you.
Delivering natural solutions at scale requires diverse thinkers truly committed to revaluing nature through transparent, equitable partnerships and systems change. We seek a truly diverse range of applicants from around the world by career stage, background, and approach.
The ideal candidate will play a crucial role in developing cutting-edge algorithms, and models to apply Computer Vision and Object-based Recognition, and other machine learning tools to remote sensing data to better understand, describe and analysis complex ecosystems and landscapes. As a Machine Learning Specialist, you will be responsible for designing advanced analytical models, developing, and implementing robust and scalable models to enhance performance and accuracy, guiding the team members to integrate the new tools in their daily workstream.
The successful candidate will possess a combination of technical expertise in machine learning, remote sensing, and computer vision, as well as strong analytical and problem-solving skills.
This position will be remote and requires excellent communication skills, technical knowledge, and a passion for the environment.
What are the main responsibilities of the role?
What do we expect from you?
Requirements:
Strong background in machine learning, deep learning, and computer vision.
Proficiency in programming languages such as Python and familiarity with machine learning frameworks/libraries such as TensorFlow, PyTorch, or Keras.
Experience with remote sensing data, including satellite imagery, LiDAR, or aerial imagery.
Solid understanding of object-based recognition techniques and image segmentation algorithms.
Excellent problem-solving skills and the ability to work independently and as part of a team.
Strong communication and presentation skills.
Excellent written and verbal communication skills.
Experience working remotely
Nice to have:
Experience with specialized remote sensing libraries or tools like GDAL.
Experience in remote sensing data analysis, particularly in land cover change detection and classification using radar, optical sensors, and high-resolution imagery.
What do we offer?
Shared purpose, culture, and values.
Unbeatable work flexibility and balance (global team, remote working)
On-the-ground work in the most iconic nature landscapes of our planet.
A truly diverse team of colleagues, partners, and clients.
An agile team, with unrivalled experience and track-record.
Competitive salary and benefits package.
If you are passionate about working with data, enjoy solving complex problems, and have the required skills and experience, we would love to hear from you. Join our team and contribute to building robust data solutions that drive our organization's success.
Note: This job description is intended to convey essential responsibilities and requirements and is not an exhaustive list of tasks. Other duties may be assigned as deemed necessary by the company.
Starting date: ASAP
Location: Remote, UK
Revalue Nature Ltd is an equal opportunity employer that values diversity and encourages people of all ethnic & racial origins, gender identities, sexual orientations, religions & ideologies, socio-economic statuses, educational backgrounds, ages, and individuals of all abilities to apply.
Applicants must be legally authorized to work in their country of residence. Revalue is unable to sponsor or take over sponsorship of an employment visa at this time.
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To apply, please submit your resume and relevant portfolio or projects showcasing your skills.
Full Time