Graduate AI Engineer - Market Intelligence

About the Role

Join Permutable as a Graduate AI Engineer and contribute to building advanced AI systems that analyze global markets. Our platform processes vast amounts of multilingual news, economic data, and geopolitical information, converting them into explainable, actionable signals utilized by institutional investors, banks, and trading teams worldwide. With coverage of over 70 assets and analyzing more than one million narratives daily across 80+ languages, we were recognized as Hedgeweek's Technology Provider of the Year: Innovation in 2026.

What You'll Do

• Design, train, and evaluate machine learning and NLP models on extensive textual datasets.
• Develop systems for classification, entity resolution, sentiment analysis, narrative clustering, information extraction, and semantic search.
• Experiment with transformer architectures, embeddings, retrieval mechanisms, and large language models.
• Create robust evaluation frameworks to assess accuracy, latency, consistency, and production performance.
• Perform detailed error analyses and implement improvements to models.
• Monitor live model behavior and investigate performance variations.
• Collaborate with engineers, data scientists, market analysts, and product teams to tackle commercial challenges.
• Clearly communicate technical insights to both technical and non-technical stakeholders.
• Contribute actively to research directions, product design, and engineering standards.

Success Milestones

• Gain a thorough understanding of Permutable's data, models, and architecture within your first months.
• Deliver improvements to existing models, evaluation methods, or data infrastructure.
• Reproduce and evaluate historical experiments using point-in-time data.
• Present findings and recommendations to the broader technical team.
• Advance to owning models, services, or technical streams; initiate original experiments and launch new features.
• Engage directly with market analysts and end users in institutional workflows.
• Mentor new graduate engineers as the team grows.

Who We're Looking For

We welcome recent graduates or those finishing their degree within two years, particularly from quantitative disciplines such as computer science, AI, machine learning, mathematics, physics, engineering, data science, computational linguistics, or related fields. Candidates should demonstrate:

• Proficiency in Python programming.
• Solid knowledge of algorithms, data structures, and software development practices.
• Strong foundation in probability, statistics, linear algebra, and machine learning concepts.
• Experience with at least one machine learning framework.
• A systematic approach to testing ideas rather than relying solely on intuition.
• The ability to independently dissect complex technical problems and make progress.
• Effective communication skills both verbally and in writing.
• Intellectual curiosity and a drive to understand system mechanics.
• Confidence in questioning assumptions and defending technical decisions.
• Motivation to thrive in a fast-paced startup setting with evolving priorities.

Additional Qualifications That Impress

• Completion of challenging dissertations or research projects.
• Internship experience involving software engineering, machine learning, or quantitative research.
• Noteworthy personal or academic projects surpassing standard coursework.
• Open-source contributions or a well-maintained GitHub repository.
• Exposure to NLP, transformers, LLMs, time-series analysis, or information retrieval.
• Participation in competitive programming, hackathons, or data science competitions.
• Academic publications or research assistant roles.
• Experience handling large, multilingual, or noisy datasets.
• Practical projects involving critical modelling or engineering compromises.

Helpful but Not Mandatory Skills

• Knowledge of PyTorch, TensorFlow, JAX, or scikit-learn.
• Familiarity with Hugging Face transformers and embedding techniques.
• Experience with vector search or retrieval-augmented generation.
• SQL and large-scale data processing skills.
• Hands-on experience with cloud platforms like AWS.
• Understanding of containerization, APIs, and production deployments.
• Use of experiment tracking and model monitoring tools.
• Interest in financial markets, economics, energy commodities, or time-series modeling.
• Experience with distributed systems and multilingual NLP.

Why Work at Permutable?

Contribute directly to live, impactful products used by major financial institutions rather than theoretical exercises. Take on meaningful responsibilities from the outset, gaining exposure across research, engineering, production, and deployment. Benefit from close mentorship within a collaborative startup culture that values initiative and continuous improvement. Grow into more complex roles and shape your technical career as the company expands. Enjoy a supportive team environment with regular social events and shared learning opportunities.

Ideal Candidate Traits

• Desires more ownership and responsibility than traditional graduate schemes provide.
• Enjoys balancing research challenges with practical engineering applications.
• Thrives tackling complex, open-ended problems.
• Values understanding the real-world impact of their work.
• Prefers a high-trust environment with rapid learning and feedback.
• Eager to help build a growing company rather than occupy a limited role.