Graph ML Engineer
- 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.
- Collaborate with cross-functional teams including data engineers, product managers, and domain experts.
- 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
- 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.
- (Bonus) PhD-level (or post-graduate research) experience in Computer Science, Machine Learning, Data Science, or a related quantitative field.
- (Bonus) Relevant publications in top venues in the field.
- (Bonus) Familiarity with agent-based systems and multi-agent AI frameworks (e.g. LangGraph, CrewAI) (e.g. LangGraph, CrewAI)
- 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
- Flexible, hybrid approach to working from home and in the office where applicable
- Focus on wellness and employee health through stipends and dedicated wellness programming
- Purposeful career development programs with reimbursement provided for educational certifications
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