6 of 6 SpaCy Jobs in the UK

Expert: Deep proficiency in Python for production-level Machine Learning and NLP. Frameworks & Tools: ML/DL: TensorFlow, PyTorch, or Hugging Face. Processing: OpenCV, Spacy, Regex, and OCR technologies. DevOps/Security: Experience delivering secure, resilient code and managing APIs. Nice to Have: Knowledge of PostgreSQL for data management. Experience ...

proposals, estimates, and delivery approaches for GenAI opportunities.QualificationsProgramming & Libraries: Deep proficiency in Python and experience with AI/ML/NLP libraries (e.g., transformers, spaCy, NLTK).LLM Expertise: Experience developing applications with state-of-the-art LLMs (e.g., GPT, Llama, Mistral, Claude), including prompt engineering and fine-tuning.GenAI & Agentic Frameworks ...

Knowledge Graphs and architecting LLM-powered solutions.* Familiarity with financial data, applications, and specific industry challenges.* Expertise in NLP libraries such as nltk and SpaCy and proficiency in unstructured text analysis.* Demonstrable leadership capabilities and experience in mentoring or leading a team.**What's In It For You**At FactSet ...

Experience with enhancing and scaling event-driven architectures. Familiarity with financial data, applications, and specific industry challenges. Expertise in NLP libraries such as NLTK, spaCy, or GLiNER and proficiency in unstructured text analysis. Demonstrable leadership capabilities and experience in mentoring or leading a team. What ...

from many sources. Python + ML/NLP stack High quality production code in Python . Libraries such as NetworkX , TensorFlow or PyTorch , NLTK, spaCy, Hugging Face, BERT , Pandas, NumPy, scikit learn . Graph based ML familiarity: link prediction, anomaly detection, traversal, community detection. NLP/NLU skills: entity/ ...

RNNs, LSTMs, and transformers Experience building automated data pipelines Hands-on experience with LLM tooling and libraries (e.g., Hugging Face Transformers/PEFT, tokenisers, spaCy or similar) Experience shipping NLP systems: prompt engineering, fine-tuning (e.g., LoRA/PEFT), vector search, and RAG-based services Great knowledge of NLP algorithms ...