Space Intelligence Engineer

About Little Place Labs

Little Place Labs is revolutionizing how satellites process and deliver intelligence from space.

We specialize 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 transform satellites into 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 orbit.

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

Our rapidly growing team of mission-driven, space enthusiasts is passionate, innovative, and committed to a better future for planet Earth, the little place that we all call home.

Position Summary:

As a Data Scientist, you will be part of the India development team of the LPL's space data analytics product Orbitfy, exploring different use cases for the technology, and working closely with the CTO to strategize the product and the company's roadmap for the next 3-4 years.

Little Place Lab's data science team is the heart and the brain of our product development, offering space-derived analytics as the source of truth for key stakeholders so they can make critical and timely decisions.

Key Responsibilities:

• Use modern AI tools to enhance productivity across the data science lifecycle.
• 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: Work 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 LPL's machine learning modules on schedule for satellite missions or user trials.
• Work on the deployment of LPL's 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 Little Place Labs' position in edge-based space intelligence.

Requirements:

To succeed in this role, you must have:

• 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:

You should have strong proficiency in Python, along with experience in frameworks like TensorFlow, PyTorch, OpenCV.

Additionally, you should have:

• General Software engineering skills: cloud infrastructure, Docker, git best practices, etc.
• Experience with architectures such as CNNs, ViTs, GANs and foundational models etc.
• Experience with model compression is a plus.

Domain Knowledge:

Familiarity with satellite imagery and remote sensing is preferred, but not mandatory if you have a strong ML background.

Soft Skills:

Excellent communication skills, ability to work independently in a remote-first setup, and a problem-solving mindset are essential for this role.