Satellite Edge Computing Expert

2 days ago

Nashik, Maharashtra, India beBeeMachineLearning Full time ₹ 1,70,00,000 - ₹ 2,19,00,000

At the forefront of a revolutionary movement, we're reimagining how satellites process and deliver intelligence from orbit. Specializing in satellite edge computing, our advanced solutions enable real-time analysis, rapid decision-making, and a significant reduction in data downlink needs.

Our vision is to empower satellites as autonomous, intelligent systems that don't just capture data, but interpret it instantly. This capability unlocks critical advantages across defense, environmental monitoring, and global communications, providing insights with speed, efficiency, and security right from space.

Job Responsibilities
  • Design and implement cutting-edge computer vision and machine learning models for satellite imagery (optical, SAR, multispectral, hyperspectral, thermal).
  • Train and fine-tune deep learning models for edge deployment (on-board satellites), balancing performance with efficiency, power, and computational constraints.
  • Provide model operations, orchestration, and workflow best practices.
  • Cross-functional collaboration: work with GIS engineers, software teams, and product managers to integrate machine learning solutions into a broader pipeline.

As a machine learning expert, you will work closely with the CTO to strategize the product and company roadmap for the next 3-4 years. You will collaborate with the engineering, product, and CTO teams to apply sophisticated modeling techniques to a modern data stack and build the future of Space Edge Computing.

Requirements
  • Bachelor's or Master's in Computer Science, Data Science, Artificial Intelligence, or a related field.
  • 3–8 years in data science, with demonstrated hands-on experience in computer vision, image processing, or machine learning.
  • Technical skills:

Strong in Python; experience with frameworks like TensorFlow, PyTorch, OpenCV. General software engineering: cloud infrastructure, Docker, git best practices, etc. Exposure to C/C++, CUDA, ONNX, TensorRT, OpenVINO, or FPGA acceleration is a plus. Experience with architectures such as CNNs, ViTs, GANs and foundational models is desired.

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