Job Description

We are seeking a talented and experienced Machine Learning Researcher to join our team of dedicated professionals As a Machine Learning Researcher, you will play a pivotal role in implementing and refining deep learning models and frameworks for various applications such as scene/semantic/panoptic segmentation, object classification, and synthetic data generation using earth observation data in the agriculture and infrastructure domains Your work will contribute to solving critical problems in land use and crop classification, change monitoring, disaster management, and more You will have the opportunity to apply your skills in a collaborative and innovative environment, contributing to the enhancement of decision-making processes that impact millions of lives Responsibilities: Implementing deep-learning models and/or frameworks that can be used in scene/semantic/panoptic segmentation, object classification, and synthetic data generation using earth observation data in the agriculture and infrastructure domain. Design and implement performance evaluation 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 the target and data shifts happening in the domain. Building models to solve open research problems on LULC, crop classification, change monitoring, and disaster management, etc from earth observations. Define and implement performance metrics for the research problems and be very methodical / organized with experiment management and performance evaluations. Qualifications and Experience: 5-8 years of experience in machine learning-based data product research and development in addition to a relevant educational background in the field of Computer Science, Engineering, Machine Learning, etc. Experience with tools/frameworks from theoretical and practical aspects of computer science and ML/DL. This includes probability, statistics, learning theory, etc. Prior experience working with statistical modeling techniques and deep learning fundamentals, such as CNN, RNN, Transformers, GANs etc. including sequence networks e.g. 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 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 problems. Educational Qualifications: Master s degree or Ph.D. in Engineering, Statistics, Mathematics or Computer Science, Machine Learning/Deep Learning domains. Benefits - Why Us Opportunity to work on a unique and futuristic technology setup. Flat organizational structure and accessibility. Best in-class leave policy. Additional allowances for learning, skill development, broadband, medical insurance coverage, etc.

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