Advanced Machine Learning Researcher for Earth Observation
2 weeks ago
We are seeking an experienced machine learning professional with expertise in deep learning and statistical modeling for earth observation data applications. This role involves developing models for segmentation, object classification, crop monitoring, and disaster management using Python, ML frameworks such as TensorFlow and PyTorch.
About SatSure:
SatSure is a decision intelligence company that specializes in creating insights from earth observation data accessible to all. We want to make a difference in the developing world by leveraging our technology to solve problems in agriculture, infrastructure, and climate action.
Key Responsibilities:
- Implementing deep-learning models and/or frameworks for scene/semantic/panoptic segmentation, object classification, synthetic data generation using earth observation data in agriculture and infrastructure domains.
- Design and implement performance evaluations frameworks for incremental and step function improvements.
- Exploring and developing new methods for improving detection/classification performance.
- Building model monitoring and active learning pipelines to address target and data shifts happening in the domain.
- Building models to solve open research problems on LULC, crop classification, change monitoring, and disaster management using earth observations.
- Define and implement performance metrics for research problems and be methodical with experiment management and performance evaluations.
Requirements:
- A Master's degree or PhD in Engineering, Statistics, Mathematics, or Computer Science, with expertise in machine learning/deep learning domains.
- 5-8 years of experience in machine learning-based data product research and development, along with relevant educational background in Computer Science, Engineering, or Machine Learning.
Must-Haves:
- Experience with tools/frameworks from theoretical and practical aspects of computer science and ML/DL, including probability, statistics, learning theory.
- Prior experience working with statistical modeling techniques and deep learning fundamentals, such as CNN, RNN, Transformers, GANs, etc., including sequence networks like LSTMs.
- Proficiency in any programming language, preferably Python, with hands-on experience in using ML frameworks such as TensorFlow, PyTorch, PyTorch Lightning, MxNet, etc.
- Ability to design, develop, and optimize machine learning/deep learning models.
- Knowledge of applying ML for earth observation data is desirable.
- An appetite for research and implementing innovative solutions for complex problems.
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:
- Intro call.
- Assessment.
- Presentation.
- Interview rounds (ideally up to 3-4 rounds).
- Culture Round / HR round.
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