Unlocking Space Intelligence with Machine Learning Expertise

1 week ago

Thāne, Maharashtra, India beBeeMachineLearning Full time ₹ 20,00,000 - ₹ 40,00,000

Revolutionizing satellite data processing and intelligence from orbit, our team specializes in edge computing solutions that process data directly on board. This unlocks critical advantages across defense, environmental monitoring, and global communications, providing insights with speed, efficiency, and security.

Based across the US, Europe, and India, our rapidly growing team of space enthusiasts works on solving complex challenges in earth observation, space situational awareness, and autonomous satellite operations.

Job Overview

We are seeking a highly skilled Data Scientist to join our development team for a cutting-edge space data analytics product.

The successful candidate will explore different use cases for the technology, work closely with our CTO to strategize the product and company roadmap, and apply sophisticated modeling techniques to a modern data stack.

Leveraging AI tools in day-to-day workflows will be key to boosting productivity and accelerating results.

Excellent communication skills are required to coordinate with global teams and external partners.

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.
  • Work with GIS engineers, software teams, and product managers to integrate ML solutions into the broader pipeline.
  • Stay ahead of emerging trends in Edge AI, ML, and remote sensing, and translate them into practical solutions for space applications.
  • Process large, complex datasets from diverse sensors; design robust preprocessing, augmentation, and feature extraction workflows.
  • Clearly articulate technical concepts, results, and trade-offs to both technical and non-technical stakeholders in a distributed team.
  • Ensure robustness, reliability, and reproducibility of solutions through systematic testing, benchmarking, and validation.
Success Metrics
  • Delivery of machine learning modules on schedule for satellite missions or user trials.
  • Deployment of products for multiple satellite missions.
  • Productivity gains and accelerated project outcomes through the adoption of AI tools.
  • Effective collaboration and communication across distributed teams.

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