Satellite Data Engineer

2 weeks ago

Ellore, Andhra Pradesh, India beBeeDataScientist Full time ₹ 40,00,000 - ₹ 60,00,000

We are a cutting-edge technology company reimagining how satellites process and deliver intelligence from orbit.

About Our Team

This is a remote-first role, requiring excellent communication skills to coordinate with global teams and external partners.

You will work closely with engineering, product, and leadership to apply sophisticated modeling techniques to a modern data stack and build the future of Space Edge Computing.

Key Responsibilities
  • Use modern AI tools to enhance productivity across the data science lifecycle (data wrangling, model design, testing, documentation, etc.).
  • 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 our 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.
  • Data Handling: Process large, complex datasets from diverse sensors; design robust preprocessing, augmentation, and feature extraction workflows.
  • Communication & Reporting: Clearly articulate technical concepts, results, and trade-offs to both technical and non-technical stakeholders in a distributed team.
  • Quality & Validation: Ensure robustness, reliability, and reproducibility of solutions through systematic testing, benchmarking, and validation.
Success Metrics
  • Delivery of our machine learning modules on schedule for satellite missions or user trials.
  • Work on the deployment of our products for multiple satellite missions.
  • Demonstrated productivity gains and accelerated project outcomes through the adoption of AI tools.
  • Effective collaboration and communication across distributed teams.

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