About Jordan
I’m a Machine Learning Consultant helping companies scope and deliver impactful AI and data science projects. I enjoy thinking deeply about how to apply data-driven approaches effectively, and I can take ideas all the way from research to engineering and production.
I draw on my experience leading deep learning at Chattermill AI (clients include Uber and Amazon), where I’ve built scalable systems using bespoke LLMs, retrieval-augmented generation (RAG), semantic search, recommender systems, and agentic workflows. I’ve also worked at the frontier of AI research and published at top conferences and journals.
I have expertise in many areas of Deep Learning and Machine Learning
• Recommender systems
• Retrieval Augmented Generation (RAG) & semantic search
• Bespoke model training and fine-tuning (up to 100B params)
• Reinforcement learning & agents
• NLP tasks: text classification, entity recognition,
• Traditional data science (tabular data, gradient boosting) & predictive modelling
Example use cases I can support:
• 🗣️ Customer Support: auto-routing inquiries to the right experts, knowledge base Q&A systems to cut service time.
• 🛍️ PIM & Product Categorization: automated enrichment and tagging pipelines.
• 📊 Market Intelligence: real-time categorization of news/events to track market dynamics.
English
Native or bilingual
Remote only
Primarily works remotely
Experience
- Chattermill AILead Deep Learning Scientist / EngineerDecember 2021 - Today (4 years and 6 months)- Lead ML pipeline design and execution to ensure business value, directing the MLOps team and working closely with Product and Engineering.- Translate novel research and academic papers in the customer feedback space into robust production code.- Research and productionize pipelines combining bespoke generation/classification models, embeddings, LLMs, clustering techniques, and traditional NLP.- Delivered retrieval-augmented generation systems for the flagship RAG product, as well as Reranker, Automatic Speech Recognition and translation services.- Developed bespoke semantic search and product classification solutions based on embeddings, enabling expansion and deal flow in a new vertical: PIM and product categorization.
- LAIONML ResearcherOctober 2022 - March 2024 (1 year and 5 months)- Actively carrying out ML engineering and research for core LAION NLP projects: OpenAssistant, Mixture of Experts, and Long-context Summarization.- Collaborating closely on work with researchers from Nous Research, Hugging Face, Together AI.- Trained multi-gpu/multi-node models up to 70B parameters on numerous A100s/H100s in HPC environments. Granted selected access to the Ezra-1 UltraCluster (high quotas, non-preemptible) for advanced ML work.
- Ontocord.aiResearch EngineerJuly 2023 - January 2024 (6 months)- Research Engineering in developing mixture of expert systems and multi-modalmodels. Conducted dataset processing and training on the JUWELS Booster andLUMI supercomputers.- Research Engineering state-of-the-art multi-modal models; managed datasetconstruction, data pre-processing, and data augmentation.
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Education
- MSc Computing (Machine Learning & A.I)Imperial College London202192%, Prize Winner with first author work with DeepMind at EMNLP
- B.Sc. MathematicsDurham University2017