Machine Learning Researcher
1 week ago
About KaleidEO
KaleidEO, a subsidiary of SatSure, is investing in launching its own fleet of earth observation satellites. We are seeking an Image Processing wizard to own and nurture the logical pipeline that delivers the best geospatial images and products.
SatSure is a deep tech, decision Intelligence company that works primarily at the nexus of agriculture, infrastructure, and climate action creating an impact for the other millions, focusing on the developing world. We want to make insights from earth observation data accessible to all.
The synergy of KaleidEO and SatSure aims to bring a new dimension to the earth observation industry by being the only full-stack company from India, to have satellites in space to deliver insights on the ground.
If you are interested in working in a space tech analytics domain driven by cutting-edge technology on the edge as well as on the ground for solving complex data problems using Multi-Sensor Earth Observation data you will have the freedom to work on innovative ideas and be creative with no hierarchies, KaleidEO us the place for you.
Role & Responsibilities:
To Implement deep-learning models and/or frameworks that can be used in scene/semantic/panoptic segmentation, object classification, and synthetic data generation using High-Resolution Earth Observation Data.
To Design and implement performance evaluation frameworks for incremental and step-function improvements.
To Explore and develop new methods for improving detection/classification performance.
To Build models monitoring and active learning pipelines to address the target and data shifts happening in the domain.
To Build models to solve open research problems on complex image preprocessing, computer vision, object identification, segmentation, change monitoring, multi-source data fusion, etc. from High-Resolution Earth Observation data sources.
To Define and implement performance metrics for the research problems and be very methodical / organized with experiment management and performance evaluations.
Qualifications
Master’s degree or PhD in Engineering, Statistics, Mathematics or Computer Science, Machine Learning / Deep Learning domains.
4-5 years of industrial experience in machine learning-based data product research and development in addition to a relevant educational background in the field of Computer Science, Mathematics, Engineering, or Machine Learning.
Must-Have
Experience with tools/frameworks from theoretical and practical aspects of computer science and ML/DL. This includes calculus, probability, statistics, learning theory, etc.
Prior experience and core foundational knowledge on working with statistical modeling techniques and deep learning fundamentals, such as CNN, RNN, Transformers, GANs, etc. include sequence networks eg LSTMs
Proficiency in Python or C++, with hands-on experience in using ML frameworks such as Tensorflow/Pytorch, Pytorch Lightning, MxNet, etc .
Good to Have
Ability to design, develop, and optimize for machine learning/ deep learning models.
Knowledge of the application of ML for earth observation data is good to have.
Appetite for research and implementing innovative solutions for complex problem.
Benefits:
Medical Health Cover for you and your family including unlimited online doctor consultations.
Access to mental health experts for you and your family.
Dedicated allowances for learning and skill development.
Comprehensive leave policy with casual leaves, paid leaves, marriage leaves, bereavement leaves.
Twice a year appraisal.
Interview Process:
Introductory call
Interview rounds (ideally up to 3-4 rounds)
Culture Round / HR round.
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