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Junior Machine Learning Scientist – Remote Sensing

Remote / Online - Candidates ideally in
Singapore
Listing for: SGInnovate
Full Time, Remote/Work from Home position
Listed on 2026-01-06
Job specializations:
  • IT/Tech
    Data Scientist, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 60000 - 80000 SGD Yearly SGD 60000.00 80000.00 YEAR
Job Description & How to Apply Below

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 cost-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, CI/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 (CI/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

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