The Role
Develop and productionize computer vision and machine learning models for large-scale geospatial and satellite imagery applications. Own projects end to end, including dataset creation, experimentation, model training, evaluation, deployment, and monitoring. Work with Python, PyTorch, distributed training infrastructure, and large data pipelines while collaborating with MLOps, platform, product, and geospatial teams.
Summary Generated by Built In
About SatSure
SatSure is a deep tech, decision intelligence company working at the nexus of agriculture, infrastructure, and climate action — creating impact for the other millions, with a focus on the developing world. As part of this mission, we're building geospatial foundation models that learn directly from Earth observation data — optical, SAR, and elevation — at scale. This role sits at the heart of that effort: architecting and training large-scale models that can generalize across geographies, sensors, and time. You'll be shaping the core intelligence layer that powers insights for millions, not just fine-tuning someone else's model.
Role:
We're looking for a Data Scientist with strong fundamentals in computer vision and machine learning to work on geospatial problems at a planetary scale. You'll develop models that turn satellite imagery into a structured, actionable understanding of the Earth's surface- work that directly impacts how decisions are made across agriculture, forestry, climate, and beyond.
This is a hands-on IC role. You'll own problems end-to-end: from formulating hypotheses and building datasets to training models, validating them rigorously, and shipping production-ready systems. You'll work with terabytes of multi-temporal, multi-sensor imagery and build solutions that generalise across geographies, seasons, and sensing modalities.
Responsibilities:
- Develop and ship computer vision models for tasks such as semantic segmentation, change detection, super-resolution, and temporal sequence modelling.
- Own the full lifecycle of ML projects: problem scoping, data pipeline design, model development, evaluation, deployment, and monitoring.
- Design experiments rigorously, define meaningful metrics, and calibrate them against business outcomes.
- Write clean, production-grade code in Python/PyTorch. Work with distributed training infrastructure and large-scale data pipelines.
- Collaborate closely with product, MLOps, platform, and geospatial teams to translate ambiguous real-world problems into well-scoped technical solutions.
- Communicate findings clearly through internal documents and presentations.
Must Have
- 3+ years of applied ML/Computer Vision experience, or PhD with 1+ year of post-degree experience, in CS, EE, or a related field.
- Strong fundamentals in semantic/instance segmentation, object detection, and encoder-decoder and transformer architectures.
- Proven experience taking models from prototype to production.
- Proficiency in PyTorch and Python. Familiarity with distributed training and MLOps tooling.
Good to Have
- Experience with generative models (GANs, diffusion), self-supervised and contrastive learning, domain adaptation, semi-supervised learning, or model compression (distillation, pruning, quantisation).
- Experience with geospatial or remote sensing data (satellite imagery, multi-spectral or SAR data, temporal modelling).
- Exposure to agricultural applications (crop classification, crop monitoring) or forestry applications (canopy height estimation, deforestation monitoring).
- Research publications at reputed venues or patents.
- Experience with foundation models, representation learning, or cross-modal fusion.
Benefits:
- Medical Health Cover for you and your family, including unlimited online doctor consultations
- Access to mental health experts for you and your family
- Dedicated allowances for learning and skill development
- Comprehensive leave policy with casual leaves, paid leaves, marriage leaves, bereavement leaves
Skills Required
- 3+ years of applied machine learning or computer vision experience, or a PhD in computer science, electrical engineering, or a related field with 1+ year of post-degree experience
- Strong fundamentals in semantic segmentation, instance segmentation, object detection, encoder-decoder architectures, and transformer architectures
- Experience taking machine learning models from prototype to production
- Proficiency in Python and PyTorch
- Familiarity with distributed training and MLOps tooling
- Experience with generative models, self-supervised learning, contrastive learning, domain adaptation, semi-supervised learning, or model compression
- Experience with geospatial or remote sensing data, including satellite imagery, multispectral data, SAR data, or temporal modeling
- Exposure to agricultural or forestry applications
- Research publications at reputed venues or patents
- Experience with foundation models, representation learning, or cross-modal fusion
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The Company
What We Do
SatSure is a deep-tech decision-intelligence company working at the intersection of agriculture, infrastructure, and climate action. It transforms satellite data into actionable insights that enable faster, smarter, and more responsible decisions, particularly in underserved regions. The company applies geospatial intelligence and advanced analytics to complex real-world challenges, supporting more informed choices across sectors while contributing to sustainable development and climate resilience worldwide.
