SatSure is looking for Data Scientists and Lead Data Scientists (Computer Vision) to build and drive the next generation of geospatial intelligence models powering critical products across agriculture, finance, infrastructure, utilities, aviation, energy, climate, and other domains.

This is a hands-on applied ML / Computer Vision role focused on solving complex Earth Observation (EO) challenges using advanced ML / CV techniques and building scalable, production-ready solutions. At the Lead level, the role additionally involves technical leadership, mentoring, ownership of multiple ML / CV initiatives, and supporting project and resource management.

About Team and Mission :

Our EO Applied Data Science team builds foundational research and applied ML systems that work across seasonal, geographic, and sensor variations - from multispectral and SAR to multi-temporal satellite data.

We have delivered high-impact Geospatial Data Science solutions across a wide spectrum of EO applications, including :

- Land Use & Land Cover Mapping

- Crop Classification

- Sowing and Harvest Progression

- Change Detection

- Route Optimization

- Satellite Image Time-Series (SITS) Classification

- Image-to-Image (I2I) Translation

- Cross-Modal Fusion

We now aim to push beyond the existing State-of-the-Art (SOTA) and build large-scale, real-time systems capable of operating on terabytes of satellite data and delivering insights that impact millions of end users, particularly across developing markets and complex or ambiguous geographies.

About SatSure :

SatSure is a deep-tech decision intelligence company that leverages Earth Observation (EO) data to solve crucial problems across agriculture, finance, infrastructure, utilities, aviation, energy, climate, and other sectors.

Our goal is to create meaningful impact for the "other millions," with a particular focus on the developing world, while making insights derived from Earth Observation data accessible to all.

With a founding team rooted in the Indian Institute of Space Science and Technology (IIST), Indian Space Research Organisation (ISRO), and Indian Institute of Remote Sensing (IIRS), along with a leadership team carrying diverse industry experience across IBM, Samsung, Intel, USC, IITKGP, IITG, and IITM, we strongly value technical innovation and scale.

If you are interested in working in an environment focused on societal impact, driven by cutting-edge technology, with the freedom to innovate and be creative in a low-hierarchy environment, SatSure is the place for you.

Roles & Responsibilities :

- Work closely with Product Owners, Applied Data Scientists, MLOps teams, Geospatial Experts, Platform Engineers, and other cross-functional stakeholders to envision solutions for real-world, ambiguous business use cases requiring low latency and high throughput.

- Identify and solve customer problems through simple and elegant solutions while working backwards from customer and business requirements.

- Quickly propose, evaluate, and validate hypotheses to help direct product roadmaps and technical decisions.

- Own time-bound, end-to-end solutioning and delivery of large-scale ML / CV applications, including problem framing, requirements and resource gathering, data collection, cleaning and annotation, data design, model development, validation, deployment, monitoring, and continuous improvement.

- Brainstorm, deep dive, implement, and debug the fundamentals of ML systems, including model architectures, loss functions, efficiency, training and serving strategies.

- Build reliable and efficient ML / CV models that generalize and scale across geographies, seasons, sensors, datasets, and business domains.

- Drive experimentation, architecture design, model development, deployment, and productionization of ML pipelines.

- Write clean, scalable, production-grade code using Python and PyTorch.

- Conduct A/B experiments wherever applicable and define appropriate Data Science output metrics, calibrating them against desired business metrics and KPIs.

- Innovate on model architectures and techniques including Transformers, generative models, diffusion models, time-series models, self-supervised learning, multimodal fusion, and temporal modeling to advance in-house geospatial ML SOTA.

- Clearly communicate technical findings, recommendations, and outcomes verbally and in writing to stakeholders from varied technical and business backgrounds.

- Engage in and initiate collaborative efforts to meet ambitious applied research, product, and client-delivery goals while maintaining strong attention to detail.

- Innovate and advance State-of-the-Art in-house solutions and communicate findings through patents, technical documents, internal whitepapers, research papers, or other forms of intellectual property, wherever applicable to the business.

- Mentor junior team members, applied scientists, and interns as applicable.

- Assist Data Science Managers with effective project and resource management, hiring, agile execution, and timely delivery while demonstrating a strong sense of ownership and accountability.

Additional Responsibilities for Lead Data Scientist :

- Own technical charters and roadmaps for multiple ML / CV initiatives.

- Lead and mentor Applied Scientists while translating complex EO problems into actionable and scalable technical solutions.

- Provide technical leadership across hypothesis generation, experimentation, architecture selection, model development, production deployment, and monitoring.

- Contribute to hiring, technical excellence, engineering / scientific best practices, and capability development across the team.

- Effectively communicate technical direction and findings to leadership, customers, and cross-functional partners.

Education :

- M.Tech / MS (Research) / PhD in Computer Science, Electrical Engineering, Electronics & Communication, Remote Sensing, or related fields, preferably from leading academic institutes, industrial research labs, or organizations.

- Exceptional undergraduate candidates with strong research and / or relevant industry experience will also be considered.

Experience :

- 4+ years of applied Machine Learning / Computer Vision experience, preferably in an industry environment.

- Proven experience taking ML models from POC - Production - Monitoring.

- 2+ years of experience in a technical leadership role involving people and project leadership.

Must-Have Technical Expertise :

Candidates should demonstrate a proven track record of relevant experience in areas such as :

- Computer Vision

- Natural Language Processing

- Learning Theory

- Optimization

- ML + Systems

- Foundation Models

Candidates should be technically familiar with some or most of the following, demonstrated through their ability to solve problems in novel scenarios :

- Transformers

- UNet

- RNNs / LSTMs / GRUs

- YOLO

- RCNN

- Encoder-Decoder Architectures

- Generative Models - GAN, VAE, Diffusion

- Self-Supervised Learning

- Contrastive Learning

- Representation Learning

- Domain Adaptation & Generalization

- Semi-Supervised Learning

- Active Learning

- Noisy-Label Learning

- Super-Resolution

- Anomaly Detection

- Clustering

- Model Compression

- Knowledge Distillation

- Pruning

- Quantization

Strong hands-on experience is also expected with:

- Python

- PyTorch

- SQL

- Distributed Systems / Spark

- MLOps

- Large-scale model training

- Data pipelines

- ML deployment and monitoring

Good to Have :

Experience or familiarity with the following would be advantageous :

- SAR data, including VV / VH

- NDVI

- FCC

- Multispectral optical data

- Temporal modeling

- Satellite Image Time-Series (SITS)

- Forecasting

- Seasonal dynamics

- Cross-modal fusion, including SAR + Optical and EO + tabular / ground data

- Geospatial datasets

- Climate models

- Foundation models

- Earth Observation analytics

First-authored publications in leading conferences or journals such as ICLR, NeurIPS, CVPR, ICCV, ECCV, ICML, AAAI, IGARSS, IEEE TGRS, or similar venues would be an advantage.

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 covering casual leave, paid leave, marriage leave, bereavement leave, and other applicable categories.