The Role
Lead large-scale computer vision and machine learning initiatives for geospatial intelligence products. Own technical roadmaps, lead and mentor applied scientists, design and deploy production ML pipelines, and develop scalable models across satellite sensors, geographies, and seasons. Responsibilities include experimentation, architecture design, monitoring, A/B testing, stakeholder communication, hiring, publications, and technical innovation involving transformers, generative models, temporal modeling, self-supervised learning, and multimodal fusion.
Summary Generated by Built In
SatSure is looking for a Lead Data Scientist (Computer Vision) to drive the next generation of geospatial intelligence models powering critical products across agriculture, finance, infrastructure, utilities, energy, and climate. This is a senior hands-on technical leadership role responsible for solving complex Earth Observation challenges using advanced ML/CV, and leading teams toward state-of-the-art, production-ready solutions.
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, Image2Image (I2I) Translation, Cross Modal Fusion etc.
We now aim to push beyond the existing SOTA and build large-scale, real-time systems that operate with terabytes of satellite data, delivering insights that impact millions of end users, especially in developing markets and more ambiguous/complex 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, and climate, to name a few. Our goal is to create meaningful impact for the “other millions,” with a focus on the developing world. We aim to make insights 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 the Indian Institute of Remote Sensing (IIRS), and a leadership team with diverse industry experience (IBM, Samsung, Intel, USC, IITKGP, IITG, IITM), we value technical innovation and scale. If you are interested in working in an environment focused on societal impact, driven by cutting-edge technology, and offering the freedom to innovate and be creative with no hierarchies, SatSure is the place for you.
Key Responsibilities:
- Own technical charters and roadmap for multiple ML/CV initiatives.
- Lead and mentor applied scientists, mapping complex EO problems into actionable, scalable technical solutions.
- Drive hypothesis generation, experimentation, architecture design, model development, and deployment for production ML pipelines.
- Own E2E delivery of large-scale ML/CV systems - from problem framing to data design, model development, deployment, and monitoring.
- Collaborate with Product, MLOps, Platform, and Geospatial experts to convert ambiguous requirements into elegant solutions.
- Communicate technical findings to leadership, customers, and cross-functional partners with clarity and precision.
- Assist data science managers in effective project, resource management, and timely deliverables (in an agile manner), via showcasing strong sense of ownership and accountability.
- Build reliable, efficient models that scale across geographies, seasons, sensors, and business domains.
- Write clean, scalable production-grade code in Python/PyTorch.
- Conduct A/B experiments and calibrate ML metrics to business KPIs.
- Innovate on model architectures (Transformers, diffusion, generative, time-series models, self-supervision, multimodal fusion and temporal modeling) to advance in-house geospatial ML SOTA.
- Represent your work through patents, technical documents, internal whitepapers, and publications (as applicable).
- Contribute to hiring and technical excellence, including mentoring junior team members and interns.
Education :
- M.Tech/MS (Research)/PhD in CS, EE, EC, Remote Sensing, or related fields preferably from leading academic/industrial labs/institutes/corporates.
- Exceptional undergraduates with strong research/industry experience will also be considered.
Experience :
- 6+ years of applied ML/Computer Vision experience (industry preferred).
- 2+ years in a technical leadership role - people and project leadership.
- Proven experience taking ML models from POC → production → monitoring.
Must have Technical Expertise:
To be eligible for this role, we are looking for candidates with the following qualifications:
- A proven track record of relevant experience in computer vision, NLP, learning theory, optimization, ML+Systems, foundational models, etc.
- Technically familiar with some, or most of (as evidenced by problem solving skills in novel scenarios): Transformers, UNet, RNNs/LSTMs/GRUs, YOLO/RCNN/Encoder–Decoder architectures, Generative models (GAN, VAE, Diffusion), Self-supervised & contrastive learning, Representation learning, domain adaptation & generalization, Semi-/Active learning, noisy-label learning, Super-resolution, anomaly detection, clustering, Model compression: distillation, pruning, quantization.
- PyTorch, Python, SQL, distributed systems (Spark), MLOps for large-scale training, data pipelines, and deployment
Good to Have:
- SAR (VV/VH), NDVI, FCC, multispectral optical data, Temporal modeling (SITS, forecasting, seasonal dynamics), Cross-modal fusion (SAR+Optical, EO+tabular/ground)
- First-authored publications in ICLR, NeurIPS, CVPR, ICCV, ECCV, ICML, AAAI, IGARSS, IEEE TGRS, etc.
- Experience with geospatial datasets, climate models, foundation models, or EO analytics.
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
Interview Process:
- Intro call
- Assessment
- Presentation
- Interview rounds (ideally up to 3-4 rounds)
- Culture Round / HR round
Skills Required
- 6+ years of applied machine learning or computer vision experience, preferably in industry
- 2+ years of technical leadership experience involving people and project leadership
- Proven experience taking machine learning models from proof of concept through production and monitoring
- Relevant experience in computer vision, NLP, learning theory, optimization, ML systems, or foundational models
- Technical familiarity with modern machine learning and computer vision architectures, including transformers, U-Net, recurrent networks, detection models, generative models, self-supervised learning, domain adaptation, and model compression
- Proficiency with Python, PyTorch, SQL, distributed systems such as Spark, MLOps, large-scale training, data pipelines, and deployment
- M.Tech, MS Research, or PhD in computer science, electrical or electronics engineering, remote sensing, or a related field
- Experience with SAR, multispectral optical data, NDVI, temporal modeling, or cross-modal geospatial data fusion
- First-authored publications in leading machine learning, computer vision, or remote sensing venues
- Experience with geospatial datasets, climate models, foundation models, or Earth Observation analytics
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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.
