Space Intelligence Engineer

1 week ago


Thiruvananthapuram, Kerala, India beBeeMachineLearning Full time ₹ 19,90,000 - ₹ 30,15,000
Job Description

As a key member of our space data analytics product team, you will play a pivotal role in exploring various use cases for our cutting-edge technology. Working closely with the CTO, you will help strategize the product and company roadmap for the next 3-4 years.

We're seeking an individual who is hands-on, embraces AI tools in daily workflows, and leverages them to boost productivity and accelerate results. You will collaborate closely with engineering, product, and the CTO to apply sophisticated modeling techniques to a modern data stack and build the future of Space Edge Computing.

Responsibilities
  • AI-Driven Development: Utilize modern AI tools to enhance productivity across the data science lifecycle (data wrangling, model design, testing, documentation, etc.).
  • Algorithm Development: Design and implement state-of-the-art computer vision and ML models for satellite imagery (optical, SAR, multispectral, hyperspectral, thermal).
  • Model Optimization: Train and fine-tune deep learning models for edge deployment (on-board satellites), balancing performance with efficiency, power, and computational constraints.
  • Cross-Functional Collaboration: Collaborate 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.
  • 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.
  • Documentation and Reporting: Maintain detailed documentation of algorithms, models, and processes; prepare reports and presentations for technical and non-technical audiences.
Success Metrics
  • Delivery of machine learning modules on schedule for satellite missions or user trials.
  • Work on the deployment of 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.
  • Contributions that shape the product roadmap and strengthen the position in edge-based space intelligence.


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