1 to 25 of 31 SpaCy Jobs in London

Knowledge of NoSQL databases (MongoDB, Cassandra, DynamoDB), message queueing systems (Kafka, RabbitMQ), and version control systems (Git). Preferred Skills: Experience with natural language processing libraries such as NLTK, spaCy, or Hugging Face Transformers. Familiarity with time-series databases and analysis tools. Knowledge of AI model serving frameworks like TensorFlow Serving or ONNX Runtime. Experience with AI ethics and bias More ❯

in building and implementing data science and machine learning solutions to tackle business problems. Comfort with rapid prototyping and disciplined software development processes. Experience with Python, ML libraries (e.g. spaCy, NumPy, SciPy, Transformers, etc.), data tools and technologies (Spark, Hadoop, Hive, Redshift, SQL), and toolkits for ML and deep learning (SparkML, Tensorflow, Keras). Demonstrated ability to work on multi More ❯

applications, especially in NLP or classification problems. Hands on experience with ML tools like TensorFlow, PyTorch etc. Experience with data science libraries such as NLTK, Scikit-learn, SciPy, (Sci)SpaCy etc. Excellent problem-solving and programming skills in Python Excellent communication skills Preferred Qualifications & Skills: If you have the following characteristics, it would be a plus: Master's or PhD More ❯

Azure, or GCP). A Bonus: Experience with graph databases such as Neo4j, Pinecone, or Milvus. Experience building native desktop apps. Experience with NLP libraries and frameworks, such as spaCy or Transformers. Familiarity with machine learning concepts and the ability to work with NLP datasets. Why Join Us: Join a pioneering joint venture at the intersection of AI and industry More ❯

thrive in a collaborative, fast-paced environment, we want to hear from you! Key Responsibilities : Develop and deploy state-of-the-art NLP models and solutions using technologies like spaCy, Transformers, and other NLP frameworks. Work with cross-functional teams to implement machine learning solutions for diverse applications, including but not limited to text embeddings, sentiment analysis, question answering, summarization … science with a strong focus on machine learning, AI, or language technologies. Technical Skills : Proficiency in Python or similar programming (intermediate level). Expertise in NLP libraries such as spaCy, Transformers, Sentence Transformers, LangChain, LangGraph, LlamaIndex, BERTopic. Hands-on experience with machine learning libraries (scikit-learn, TensorFlow, PyTorch). Experience with cloud platforms (AWS, Google Cloud, Azure) and version control More ❯

in building and implementing data science and machine learning solutions to tackle business problems. Comfort with rapid prototyping and disciplined software development processes. Experience with Python, ML libraries (e.g. spaCy, NumPy, SciPy, Transformers, etc.), data tools and technologies (Spark, Hadoop, Hive, Redshift, SQL), and toolkits for ML and deep learning (SparkML, Tensorflow, Keras). Demonstrated ability to work on multi More ❯

Background: Advanced degree in AI, statistics, mathematics, computer science, or a related field. Programming and Frameworks: Hands-on experience with Python, TensorFlow or PyTorch, and NLP libraries such as spaCy and Hugging Face. GenAI Tools: Practical experience with LangChain, Hugging Face Transformers, and embedding models for building GenAI applications. Prompt Engineering: Expertise in prompt engineering, including prompt tuning, chaining, and More ❯

Checkout.com is one of the most exciting fintechs in the world. Our mission is to enable businesses and their communities to thrive in the digital economy. We’re the strategic payments partner for some of the best known fast-moving More ❯

Full-time Cost Center Hierarchy: Technology CKO Department: Technology Company Description Checkout.com is one of the most exciting fintechs in the world. Our mission is to enable businesses and their communities to thrive in the digital economy. We’re the More ❯

in data science , with a focus on NLP , Generative AI and LLMs . Proficiency in Python and experience working with transformer based LLMs and NLP frameworks (e.g. Hugging Face, Spacy, Pytorch/Tensorflow etc ). Knowledge of Prompt Engineering , RAG techniques and various evaluation methodologies for integrating GenAI with search/retrieval systems and measure the quality . Experience working More ❯

years of experience in data science, with a focus on NLP, Generative AI and LLMs. Proficiency in Python and experience working with LLMs and NLP frameworks (e.g. Hugging Face, Spacy, Pytorch/Tensorflow etc). Experience with Prompt Engineering, RAG techniques and various evaluation methodologies for integrating GenAI with search/retrieval systems and measure the quality. Experience with LangChain More ❯

Machine learning experience : Familiarity with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn. Natural Language Processing (NLP) : Experience with NLP techniques and tools, such as spaCy or NLTK. Distributed systems : Knowledge of distributed systems and experience with tools like Kubernetes or Docker. Cloud services : Experience with cloud platforms like AWS, GCP, or Azure. Open source contributions More ❯

relationships with cross-functional teams. Ability to clearly communicate and present to internal and external stakeholders. Nice to have, but not essential NLP/Deep learning experience (e.g. huggingface, spaCy) Deep learning framework experience (preferably PyTorch) MLOps experience (e.g. data and model versioning, model deployment CI/CD, MLFlow/DVC) Cloud platform experience, especially from an ML standpoint (AWS More ❯

relationships with cross-functional teams. Ability to clearly communicate and present to internal and external stakeholders. Nice to have, but not essential NLP/Deep learning experience (e.g. huggingface, spaCy) Deep learning framework experience (preferably PyTorch) MLOps experience (e.g. data and model versioning, model deployment CI/CD, MLFlow/DVC) Some basic devops experience useful (kubectl, helm, etc.) Cloud More ❯

Employment Type: Permanent Private healthcare and dental insurance 25 days annual leave plus bank holidays Pension scheme with up to 8% employer contribution £2,000 annual learning and development budget Season ticket loan Annual performance-based bonus About the Role More ❯

AI and Agent-based AI systems. Proficiency in Python and experience with ML libraries such as scikit-learn, TensorFlow, PyTorch. Extensive experience with NLP techniques and libraries like NLTK, spaCy, Gensim, Transformers. Experience with version control systems (Git) and AWS. Knowledge of MLOps practices and tools. If you meet the above criteria and are available to start ASAP, please send More ❯

Generative AI and open-source models. Proven Python development experience, with a focus on ML, NLP, image processing, and OCR. Familiarity with frameworks such as TensorFlow , PyTorch , Hugging Face , SpaCy , OpenCV , and Regex . Proven ability to deploy secure, production-grade code and APIs while ensuring cybersecurity and application resilience. Nice to Have: Experience with PostgreSQL . Knowledge of Azure More ❯

part of enterprise technology stacks. DataOps/MLOps experience would be valued. Strong Python programming for modelling and/or data analysis is essential, preferably with experience using the spaCy NLP framework and BERT. Knowledge of database design as well as strong experience with SQL queries is desirable. Familiarity with R and other common languages and tools would be beneficial. More ❯

learning culture within the team. Qualifications Experience managing data pipelines and leading a data science team. Proficiency in Python and experience with LLMs and NLP frameworks (e.g., Hugging Face, Spacy, Pytorch/Tensorflow). Knowledge of Prompt Engineering, RAG techniques, and evaluation methodologies for integrating GenAI with search/retrieval systems. Experience with LangChain/LlamaIndex, vector databases (e.g., FAISS More ❯

effectively to clients and internal teams. Technical Skills: Proficiency with open-source tools and technologies. Languages & Libraries: Python, R, Pandas, NumPy, scikit-learn, XGBoost, LightGBM, statsmodels. NLP & ML Frameworks: spaCy, Hugging Face Transformers, TensorFlow or PyTorch (as applicable). Visualization tools: Plotly, Seaborn, Matplotlib, Dash, Streamlit. Preferred Qualifications: Fluency in French or German is a strong advantage for future client More ❯

and improve the performance of NLP models. Build custom language models tailored to specific industry requirements. What Were Looking For: Proven experience with NLP frameworks such as Hugging Face, spaCy, or TensorFlow. Hands-on experience working with Large Language Models (LLMs) and deploying them in production. Advanced Python skills, with the ability to develop and optimise machine learning pipelines. Experience More ❯

fairness, and compliance. Help shape the data pipeline and MLOps practices for handling sensitive legal content securely. Required Experience: Solid experience with Python and ML/NLP libraries (e.g., spaCy, Hugging Face, TensorFlow/PyTorch). Experience building NLP or document analysis solutions, ideally for legal or compliance use cases. Strong understanding of legal language, structures, and workflows (e.g., contracts More ❯

fairness, and compliance. Help shape the data pipeline and MLOps practices for handling sensitive legal content securely. Required Experience: Solid experience with Python and ML/NLP libraries (e.g., spaCy, Hugging Face, TensorFlow/PyTorch). Experience building NLP or document analysis solutions, ideally for legal or compliance use cases. Strong understanding of legal language, structures, and workflows (e.g., contracts More ❯

Management: Leverage hybrid cloud experience to manage on-premise and AWS cloud resources effectively Data Science Support: Support data science, machine learning, and AI workloads using tools like Jupyter, Spacy, Transformers, and NLTK. Big Data Platforms: Utilize big data NoSQL engines and platforms such as Hive, Impala, and Elasticsearch for data storage and processing BI and Visualization: Implement and support … focus on security and GDPR compliance. Hybrid cloud experience, specifically with on-premise and AWS cloud environments. Familiarity with data science, machine learning, and AI tools such as Jupyter, Spacy, Transformers, and NLTK. Experience with big data NoSQL engines/platforms such as Hive, Impala, and Elasticsearch. Proficiency with business intelligence and visualization tools like Tableau, Kibana, and PowerBI. Excellent More ❯

custom domains via fine tuning or RLHF. Experience in Information Retrieval systems for document question answering. Experience in day-to-day NLP for industry using Python and related toolchains (SpaCy, HuggingFace, NLTK, etc.). Published research in areas of machine learning at major conferences and/or journals. If some of the above doesn't line up perfectly with your More ❯