For over 15 years, I’ve been driven by a conviction that mathematics, computing, and thoughtful engineering can be powerful forces for positive change.
As a Senior Software Engineer with a PhD in Computational Geometry, I recently completed an intensive chapter at CarbonSpace (Dublin-headquartered, remote — 2023–February 2026), where I helped build a satellite-based platform for monitoring Net Ecosystem Exchange (NEE) — the balance of CO₂ absorbed and released by ecosystems.
I designed and built ML pipelines that fused satellite imagery (Landsat) with meteorological and soil data to predict carbon fluxes across diverse land cover types. This included architecting cloud-native data ingestion pipelines using Zarr and STAC for reproducible, lineage-tracked geospatial workflows — from raw satellite scenes through to ML-ready data cubes. On the infrastructure side, I implemented AWS Batch workflows for data ingestion, training, and inference along with the team, and enforced hexagonal architecture across the platform to keep scientific logic decoupled from cloud infrastructure.
The impact: a modern, extensible ML platform capable of estimating carbon exchange at farm and forest scale — supporting CarbonSpace’s mission to make carbon monitoring transparent and verifiable.
Before CarbonSpace, I was a key contributor at Cervest, where I co-architected a global riverine and pluvial flood risk system at 90 m resolution. I built the core flood inundation model in Julia, created Julia bindings for the C++ RichDEM library for pluvial modelling, and applied performance engineering techniques (DiskArrays, memory-mapped I/O, Zstandard compression) that made global-scale processing feasible. The work spanned flood hydrology, Bayesian statistics, and distributed computing on Kubernetes. Read more →
What Drives Me#
I believe technology should serve humanity. Whether designing memory-efficient algorithms for large-scale climate data, implementing scientific accuracy in CO2 monitoring systems, or volunteering with Solve for Good and World Resources Institute, I’m motivated by applying rigorous engineering to problems that matter.
My Expertise#
My work spans Big Data, Computational Geometry, Image Processing, Geospatial Computing, and Healthcare Technology. I bring a passion for translating complex scientific research into well-designed, high-performance software.
I’ve built:
- 3D point cloud processing algorithms for surgical navigation
- Julia wrapper for RichDEM’s Fill-Spill-Merge C++ algorithm, used for pluvial flood modeling at Cervest
- Containerized data pipelines for climate intelligence (Argo Workflows, Pachyderm, AWS Batch)
- ML platforms with hexagonal architecture and domain-driven design
- CAD toolkits for medical device manufacturing
Through systematic code review, architectural patterns, and platform modernization initiatives, I help teams build systems that are not just functional—but maintainable, scalable, and scientifically rigorous.
Looking Forward#
I’m currently open to new opportunities in software engineering projects with high social impact, particularly in interdisciplinary environments where curiosity, continuous learning, and collaboration are valued as much as technical excellence.
If you’re working on challenges at the intersection of:
- Climate & Environmental Tech
- Geospatial Intelligence
- Machine Learning & Scientific Computing
- Healthcare Technology
I’d love to connect.
Based in Goa, India • Remote-first with 15+ years of distributed team experience across Europe and Asia
Download my resume • Get in touch to discuss consulting opportunities, collaborative projects, or full-time positions.