The posting
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 senior Data Scientist to serve as technical lead for a team of 4-5 scientists working on geospatial AI. You'll set the technical direction for building ML systems that interpret satellite imagery at scale across agriculture, forestry, and environmental monitoring.
This is a player-coach role. You'll spend significant time hands-on with research and code, while also shaping the team's roadmap, mentoring junior scientists, and ensuring the work compounds into reliable, scalable systems.
Responsibilities:
- Define and drive the technical roadmap for multiple concurrent ML/CV initiatives. Identify the highest-leverage problems and allocate effort accordingly.
- Lead research on novel architectures and training strategies, and translate findings into production systems.
- Mentor DS-1 and DS-2 scientists: help them scope problems, debug experiments, sharpen their research taste, and grow technically.
- Own end-to-end delivery of large-scale ML systems, from problem framing through data design, model development, deployment, and monitoring.
- Design robust experimental frameworks. Set standards for evaluation, reproducibility, and technical documentation across the team.
- Collaborate with product, MLOps, platform, and geospatial teams to convert ambiguous requirements into clear technical plans.
- Represent the team's work through publications and patents.
- Assist science managers in project planning, hiring, and delivery.
Must Have:
- 5+ years of applied ML/Computer Vision experience, or PhD with 3+ years of post-degree experience, in CS, EE, or a related field.
- Deep expertise in semantic/instance segmentation, object detection, encoder-decoder and transformer architectures, and temporal/sequential modelling.
- Demonstrated technical leadership: setting direction for a team, driving architectural decisions, and raising the bar on research quality.
- Experience mentoring researchers or setting technical direction for a small team.
- Track record of peer-reviewed research publications at reputed venues or patents.
- Proven experience shipping ML models from research through to production at scale.
- Proficiency in PyTorch and Python. Strong software engineering skills with clean, maintainable code. Familiarity with distributed training and MLOps tooling.
Good to Have:
- Experience with generative models (GANs, VAEs, diffusion), self-supervised and contrastive learning, domain adaptation and generalisation, super-resolution, or model compression.
- 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).
- Experience with foundation models, large-scale pre-training, 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
