Intelligent Satellite Systems Engineer

1 day ago

Shimoga, Karnataka, India beBeeMachineLearning Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
Lead Computer Vision and Machine Learning Engineer

We're reimagining how satellites process and deliver intelligence from orbit.

Our team specializes in satellite edge computing, developing advanced solutions that enable real-time analysis, rapid decision-making, and a significant reduction in data downlink needs.

Our vision is to turn satellites into autonomous, intelligent systems that interpret data instantly. This capability unlocks critical advantages across defense, environmental monitoring, and global communications, providing insights with speed, efficiency, and security right from space.

As part of our India development team, you'll work on the LPL's space data analytics product Orbitfy. You'll explore different use cases for the technology and collaborate closely with the CTO to strategize the product and company roadmap for the next 3-4 years.

Key Responsibilities
  • Design and implement state-of-the-art computer vision and ML 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 MLOps, orchestration, and workflow best practices.
  • Cross-functional collaboration with GIS engineers, software teams, and product managers to integrate ML solutions into Orbitfy's broader pipeline.
  • Innovation & research: stay ahead of emerging trends in Edge AI, ML, and remote sensing, and translate them into practical solutions for space applications.

Success metrics include delivery of LPL's machine learning modules on schedule for satellite missions or user trials, effective collaboration and communication across distributed teams, and contributions that shape the product roadmap and strengthen Little Place Labs' position in edge-based space intelligence.

Requirements
  • Education: Bachelor's or Master's in Computer Science, Data Science, Artificial Intelligence, or a related field.
  • Experience: 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.
  • Domain knowledge: familiarity with satellite imagery and remote sensing preferred (but not mandatory if strong ML background).

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