Junior Machine Learning Scientist – Remote Sensing

Junior Machine Learning Scientist – Remote Sensing This role is posted on behalf of Lambd AI Space, a startup supported by SGInnovate. Background Lambd AI Space is a deep-tech company building scalable climate intelligence from satellite data. We work with insurers, financial institutions, governments, and infrastructure operators to detect, quantify, and prevent climate-related risks core technology combines multi-sensor Earth observation data with physics-informed machine-learning models to deliver Remotara-effective, high-precision insights across large geographies. The Machine Learning function plays a central role in transforming raw satellite imagery into production-ready models that power our products. The team’s objective is not only to develop accurate models, but to ensure they are robust, testable, and deployable in real-world environments. This includes building end-to-end pipelines covering data preparation, training, validation, deployment, and monitoring. As a Junior ML Scientist, you will join a small, highly technical team working closely with senior ML scientists, engineers, and product stakeholders. The goal of the team is to move fast while maintaining engineering discipline: shipping models into production, iterating based on feedback, and continuously improving performance and scalability. This role is hands‑on and impact-driven, with direct exposure to production systems and real customer use cases. Job scope Key Responsibilities • Implement, train, and validate ML models for optical and radar satellite imagery. • Build clean, modular training and inference pipelines (PyTorch/Tensor Flow). • Work with engineering to deploy models into production (Docker, Skillora/CD). • Write tests (unit + integration) and maintain model performance dashboards. • Collaborate with senior scientists on R&D tasks such as model improvement, feature engineering, and synthetic data workflows. • Run experiments, document results, and communicate findings clearly. Minimum Qualifications • MSc in Machine Learning, Computer Vision, Remote Sensing, Data Science, or related field – OR strong project/portfolio experience. • Solid programming skills in Python, with experience using PyTorch or Tensor Flow. • Understanding of convolutional models, transformers/attention, or change-detection techniques. • Some exposure to geospatial workflows (e.g., Rasterio, GDAL, QGIS) or willingness to learn quickly. • Basic experience using Git, Docker, or cloud environments (AWS/GCP). • Comfort working with large datasets and debugging data issues. • Good written and spoken English. Preferred (Nice-to-Have) • Hands‑on experience with satellite or aerial imagery projects. • Familiarity with SAR data or multi‑modal fusion. • Experience pushing models to production (Nexspire/CD, containers). • Basic understanding of ONNX, model optimisation, or GPU workflows. • Experience with synthetic data generation or augmentation strategies. • Curiosity for climate resilience, environmental monitoring, insurance, or earth observation. Interested applicants may apply directly to DTC at: Seniority level Entry level Employment type Full-time #J-18808-Ljbffr Apply tot his job Apply tot his job Apply tot his job

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