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Revolutionizing supply chain discovery and risk analysis by developing and deploying cutting-edge machine learning solutions to uncover hidden risks, enable due diligence, and enhance transparency across global supply chains.

Requirements

• Strong and proven programming skills (Python preferred, but other languages may also be considered).
• Proven experience with graph theory and graph ML algorithms (e.g., GNNs, GraphRAG, link prediction).
• Hands-on expertise with LLMs (and transformers-based models) and transfer learning, model fine-tuning, and prompt engineering.
• Strong background in building and deploying predictive ML models in production environments.
• Familiarity with agent-based systems and multi-agent AI frameworks (e.g. LangGraph, CrewAI)

Responsibilities

• Design and implement graph-based machine learning models to map and analyse complex supply chain networks.
• Develop and fine-tune Large Language Models (LLMs) for extracting and synthesizing supply chain-related data from diverse text sources.
• Build and optimize Graph RAG models
• Create predictive models to identify risk factors and forecast disruptions within supply chains.
• Contribute to the development of Agentic AI systems for dynamic and autonomous supply chain analysis and decision-making.
• Provide technical leadership in AI and Data Science, and engage with the company’s R&D culture
• Contribute to potential publications and/or IP patents

Other

• Collaborate with cross-functional teams including data engineers, product managers, and domain experts.
• Discretionary Time Off for all employees, with no maximum limits on time off
• Industry leading health, vision, and dental benefits
• Competitive compensation package
• 16 weeks of fully paid parental leave