Remote
Full Time
Client : https://energylifeglobal.com/
Role: remote (1st Contract for 3+ month then extended to continues)
Working hours :(40 hrs - Monday to Friday)
Immediate joiners prefer
Key Responsibilities
1.Data Ingestion and Processing Pipeline: Build and maintain an automated pipeline
to ingest and process raw satellite data from sources like the Registry of Open Data on
AWS, storing the results in a data lake built on Amazon S3.
2.AI Model Training & Integration Framework: Develop a framework in Python to
automate the machine learning lifecycle, including the training, validation, versioning,
and storage of models for satellite image classification (Segmentation) and thermal
risk prediction (using libraries like XGBoost). You will also integrate the UTCI
(Universal Thermal Climate Index) calculation logic using the pythermalcomfort
library.
3. Real-time Prediction API: Design and build a low-latency REST API using AWS
Lambda and API Gateway to serve real-time predictions from the AI models.
4. Frontend Core Feature Implementation: Implement the core features of the
interactive dashboard using React and Mapbox GL JS, focusing on the intuitive
visualisation of complex geospatial heatmap data.
5. Cloud Infrastructure: Design and construct the entire cloud infrastructure using
Infrastructure as Code (IaC) principles with the AWS CDK, ensuring the platform is
secure, cost-effective, and scalable.
Qualifications
Required Qualifications:
6. A minimum of 3 years of professional software development experience
7 Deep expertise in either Python-based backend development or React-based frontend
development
8. Essential, in-depth experience designing, building, and deploying services on
Amazon Web Services (AWS), with a strong command of Lambda, S3, API
Gateway, and IAM
9. A thorough understanding of REST principles and proven experience in designing
and building APIs from scratch.
10. Proficiency in containerising applications using Docker
11.Demonstrated ability to independently solve complex, open-ended technical
challenges
12.Strong communication skills to articulate technical decisions and collaborate with the
team
Preferred Qualifications:
1.Experience building complex, interactive mapping and data visualisation services
with Mapbox GL JS or similar libraries.
2. Experience with GIS data processing using libraries like GeoPandas and Rasterio, or
familiarity with Google Earth Engine.
3. Experience with ML model serving (MLOps) using frameworks like XGBoost and
Scikit-learn.
4. Proven experience with Infrastructure as Code (IaC) tools such as AWS CDK or
Terraform.
5. Previous experience in an early-stage start-up, demonstrating the ability to build a
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