AI/ML Modeler

About us

The physical commodities supply chain is valued at $27 trillion annually. We are building the first independent platform dedicated to storage location risk due diligence and are seeking innovative, out-of-the-box thinkers to join our effort.

At Sphere, our mission is to transform how commodity traders, financing banks, and supply chain participants manage risk. Our SaaS platform will integrate real-time data, actionable insights, and powerful automation to provide clients with greater transparency over significant risks and, most importantly, to help prevent fraud.

Although we are just beginning, our foundation is built on years of experience and a global network that we are ready to leverage. If you are excited by complex challenges, cutting-edge technology, and meaningful work in a mission-critical industry, we would love to meet you.

Headquartered in Singapore.

Division Summary

Our Engineering Division is the driving force behind Sphere, dedicated to modernizing commodity risk management. We design and build a scalable, secure, and intelligent platform that integrates real-time data processing, risk analytics, and workflow automation.

We are seeking a AI/ML modeler to support our creative initiatives across multiple digital platforms. The ideal candidate will possess a strong understanding of risk industry and ai modelling with high accuracy.

Why join us?

• Exciting Projects: Work on a unique platform with real-world impact
• Collaborative Team: Join a talented and friendly team that values innovation and growth
• Professional Development: Opportunities to learn and work with cutting-edge technologies (AI and Blockchain features to be implemented)
• Dynamic Environment: Be part of a thriving startup, with a hands-on mentality, that will work alongside some of the world's largest clients

Key Responsibilities

Risk Modelling & Analysis of inherent risk factors, control effectiveness and compute residual risk score

Implement Probabilistic, Bayesian and ensemble models for risk estimates

AI Governed drift identification and correction suggestion, including data drift, concept drift, predict drift

Maintaining model versioning, lineage and reproducibility

Maintain audit ready documentation

Develop AI Vision models for proofing image integrity including tampering, manipulation, forgery

Identification and classification of objects in images and video along with their attributes

Implementing CNNs, Vision Transformers, multi-modal vision models, image hashing, integrity verification

Develop model for Geospatial intelligence for facility location, cargo using GIS, satellite imagery, GPS and spatial indexing

Geofencing, external factors, anomaly detection

Supervised and unsupervised fraud detection models

Coordination with platform engineers for deployment using MLOps and exposing models using API

Performance and Quality monitoring and improvement

Preferred Qualifications and Experience

Graduate or Higher Education - preferred in machine learning, data science or related domain

Minimum experience of 4 years of relevant AI modelling

Proven experience in Machine Learning and AI modelling

Proficiency in Python ML Libraries, ML Pipelines and orchestration

Hands on experience in Computer Vision (OpenCV, CNNs, Vision Transformers, Geospatial Analytics)

Knowledge of drift detection, fraud and anomaly detection techniques

Understanding of Risk frameworks

Self-hosted LLMs and Langchain integration

Owned the model delivery framework and deploying on production

Experience in risk, compliance, insurance, logistics, supply chain, finance or security domain is a plus