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- Tasks: Design and implement innovative graph ML models for supply chain analysis.
- Company: Join Exiger, a leader in AI-driven risk management and compliance solutions.
- Benefits: Enjoy unlimited time off, competitive pay, and flexible hybrid work options.
- Why this job: Be part of a mission-driven team transforming global supply chains with cutting-edge technology.
- Qualifications: Strong programming skills and experience with graph ML and LLMs required; PhD is a bonus.
- Other info: Contribute to impactful projects and potential publications in a supportive R&D culture.
The predicted salary is between 43200 - 72000 £ per year.
We are seeking a highly skilled and innovative AI Data Scientist to join our team focused on revolutionizing supply chain discovery and risk analysis. As part of our advanced Data Science and AI group, you will develop and deploy cutting-edge machine learning solutions that uncover hidden risks, enable due diligence, and enhance transparency across global supply chains among other applications.
Key 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.
- 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
Professional Experience Required:
- 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)
We\’re an amazing place to work. Why?
- 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
#LI-Hybrid
Exiger is revolutionizing the way corporations, government agencies and banks manage risk and compliance with a combination of technology-enabled and SaaS solutions. In recognition of the growing volume and complexity of data and regulation, Exiger is committed to creating a more sustainable risk and compliance environment through its holistic and innovative approach to problem solving. Exiger\’s mission to make the world a safer place to do business drives its award-winning AI technology platform, DDIQ, built to anticipate the market\’s most pressing needs related to evolving ESG, cyber, financial crime, third-party and supply chain risk. Exiger has won 30+ AI, RegTech and Supply Chain partner awards.
Exiger\’s core values are courage, excellence, expertise, innovation, integrity, teamwork and trust.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or protected veteran status, or any other legally protected basis, in accordance with applicable law.
Exiger\’s hybrid work policy is periodically reviewed and adjusted to align with evolving business needs. #J-18808-Ljbffr
Graph ML Engineer employer: Exiger
Contact Detail:
Exiger Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Graph ML Engineer
✨Tip Number 1
Familiarise yourself with the latest advancements in graph-based machine learning and large language models. Being able to discuss recent trends or breakthroughs during your interview can demonstrate your passion and expertise in the field.
✨Tip Number 2
Network with professionals in the AI and data science community, especially those who have experience in supply chain applications. Engaging in discussions or attending relevant meetups can provide insights and potentially lead to referrals.
✨Tip Number 3
Prepare to showcase your hands-on experience with graph ML algorithms and LLMs. Be ready to discuss specific projects where you've implemented these technologies, as practical examples can significantly strengthen your candidacy.
✨Tip Number 4
Research Exiger's mission and values thoroughly. Understanding their approach to risk management and compliance will allow you to align your answers with their goals, showing that you're not just a fit for the role but also for the company culture.
We think you need these skills to ace Graph ML Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your programming skills, particularly in Python, and showcases your experience with graph theory and machine learning algorithms. Use specific examples that demonstrate your expertise in these areas.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and data science. Mention how your background aligns with the responsibilities of the Graph ML Engineer role, particularly your experience with LLMs and predictive modelling.
Showcase Relevant Projects: Include any relevant projects or publications in your application that demonstrate your hands-on experience with graph ML models and agent-based systems. This will help you stand out as a candidate with practical knowledge.
Highlight Collaboration Skills: Since the role involves working with cross-functional teams, emphasise your teamwork and collaboration skills in your application. Provide examples of how you've successfully worked with others to achieve project goals.
How to prepare for a job interview at Exiger
✨Showcase Your Technical Skills
Be prepared to discuss your programming skills, especially in Python, and any experience you have with graph ML algorithms. Bring examples of past projects where you've implemented these technologies, as this will demonstrate your hands-on expertise.
✨Understand the Company’s Mission
Familiarise yourself with Exiger's mission to revolutionise risk and compliance management. Understanding their core values and how they align with your own can help you articulate why you're a good fit for the team.
✨Prepare for Problem-Solving Questions
Expect to face questions that assess your problem-solving abilities, particularly in relation to supply chain disruptions and risk analysis. Think of specific scenarios where you've successfully identified risks or developed predictive models.
✨Engage with Cross-Functional Collaboration
Since the role involves collaboration with various teams, be ready to discuss your experience working in cross-functional environments. Highlight instances where you've effectively communicated complex technical concepts to non-technical stakeholders.
