1 to 25 of 114 scikit-learn Jobs in the UK excluding London

writing clean, efficient, and maintainable code to enable scalable and production-grade AI/ML solutions. Extensive experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch), with the ability to design, implement, and optimise scalable solutions while guiding teams in the effective use of these tools. Extensive ...

work on projects independently and own deliverables. Strong proficiency in Python for data manipulation, analysis, visualisation and data science (e.g., Pandas, NumPy, Scikit-learn). Proficiency in data querying languages (e.g., SQL). Solid understanding of software engineering best practices (version control, unit testing, code review, etc.). ...

following areas would be highly beneficial: Machine Learning and AI Engineering Generative AI and Large Language Models Prompt engineering and context engineering scikit-learn, PyTorch or TensorFlow LangChain or similar AI frameworks Cloud data platforms and services across AWS, Azure or GCP Data warehouses and modern data platforms ...

maintainable code for developing and deploying reliable AI/ML solutions in production environments. Hands-on experience using machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch) to design and implement solutions. Experience deploying AI/ML models to production systems in collaboration with engineering teams. Experience working with ...

with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. Contributions to open-source AI projects or research ...

experience with modern deep learning frameworks (e.g.PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn,XGBoost). Experience with data storage for AI, vector databases, semanticsearch,and knowledge graphs. Contributions to open-source AI projects or research publications. ...

5+ years of applied experience building production Python systems, including web/API services (Flask or FastAPI) and the ML/NLP ecosystem (scikit-learn, pandas, NumPy, spaCy, PyTorch or TensorFlow). Demonstrated experience taking machine learning models from prototype to production - training, packaging, deployment, monitoring, retraining ...

practice: Contribute to how the wider data science function approaches tooling, methodology, and model governance. Technical Environment Languages/Tools: Python (NumPy, Pandas, Scikit learn), deep learning frameworks (PyTorch/TensorFlow), SQL. MLOps: MLflow, cloud ML platforms (Azure ML, AWS SageMaker, or Databricks). Focus areas: Predictive modelling ...

environments. Essential experience includes: Strong commercial development experience with Python , including asynchronous programming. Strong knowledge of the Python machine learning ecosystem, particularly PyTorch, Scikit-learn and NumPy . Experience deploying speech technologies , ideally including both ASR and TTS models. Experience deploying, serving or optimising Large Language Models ...

with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. Contributions to open-source AI projects or research ...

with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. Contributions to open-source AI projects or research ...

experience with modern deep learning frameworks (e.g.PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn,XGBoost). Experience with data storage for AI, vector databases, semanticsearch,and knowledge graphs. Contributions to open-source AI projects or research publications. ...

object-oriented design and software engineering fundamentals: version control, code review, automated testing, dependency and environment management. Machine learning across the standard toolkit (scikit learn, pandas, NumPy, statsmodels or equivalents), with sound judgement about model selection, validation and the limits of what the data supports. MLOps ...

client projects Requirements 5+ years of experience in machine learning engineering or applied ML research Strong proficiency in Python, PyTorch or TensorFlow, and Scikit-learn Experience deploying ML models at scale using Docker, Kubernetes, or serverless Deep understanding of ML fundamentals: optimisation, regularisation, evaluation metrics Experience with cloud ...

experience with modern deep learning frameworks (e.g.PyTorch, TensorFlow),fine-tuning or distillation of LLMs (e.g. GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn,XGBoost). Experience with data storage for AI, vector databases, semanticsearchand knowledge graphs. Actively contributes to open-source AI projects, researchpublicationsand industry events ...

product managers Contribute to a culture of continuous improvement, knowledge sharing, and technical excellence Required Skills & Qualifications Strong proficiency in Python (NumPy, Pandas, Scikit-learn, or similar) Experience building data pipelines and working with structured and unstructured data Solid understanding of SQL and relational and non-relational databases ...

product managers Contribute to a culture of continuous improvement, knowledge sharing, and technical excellence Required Skills & Qualifications Strong proficiency in Python (NumPy, Pandas, Scikit-learn, or similar) Experience with React (hooks, state management, component architecture) Experience building data pipelines and working with structured and unstructured data Solid understanding ...

impact. Your Skills & Experience Strong experience deploying machine learning models into production. Advanced Python skills and experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch. Experience building and maintaining MLOps pipelines and CI/CD workflows. Strong knowledge of AWS, Azure, or GCP. Experience with ...

techniques, focused on timeseries data and text Strong programming skills in Python and experience with standard data science libraries such as pandas, numpy, scikit-learn, tensorflow, pytorch Experience working with data systems, structured and unstructured databases such as ClickHouse or MongoDB Familiarity with APIs, pipelines, kubernetes and linux ...

star schemas and Kimball methodologies Experience supporting advanced Power BI models (DAX and Power Query) Exposure to ML/AI concepts (e.g. scikit-learn, TensorFlow) or an interest in preparing data for LLMs, RAG architectures or predictive models Experience with Docker and/or Terraform (desirable) What ...

solve real-world problems in industry or academia Strong Python programming skills and deep familiarity with the Python ecosystem (i.e. pandas, numpy, scikit-learn, pytorch, pip, pytest) Demonstrated ability to lead technical teams and initiatives with strong communication and stakeholder management skills Preferred Qualifications, Capabilities, and Skills Experience ...

model prototyping to production deployment, integration, and ongoing monitoring. You are proficient in Python and its data/ML ecosystem (e.g. pandas, scikit-learn, PyTorch, TensorFlow), and you can apply statistical and machine learning techniques confidently in real-world settings. You have deployed models into live systems ...

solve real-world problems in industry or academia Strong Python programming skills and deep familiarity with the Python ecosystem (i.e. pandas, numpy, scikit-learn, pytorch, pip, pytest) Demonstrated ability to lead technical teams and initiatives with strong communication and stakeholder management skills Preferred qualifications, capabilities, and skills: Experience ...

MLOps and production deployment AI evaluation, testing and observability AI governance, model risk and engineering controls ML frameworks such as PyTorch, TensorFlow or Scikit-learn Experience operating in complex, regulated or high-risk environments would be particularly valuable. More important than any individual technology is the ability ...

Data Science, AI, Computer Science, Mathematics, Engineering, or a related field. Experience with Python and its data science ecosystem (e.g., pandas, numpy, scikit-learn). Familiarity with machine learning concepts and techniques (e.g., regression, classification, neural networks). Proactive, detail-oriented, and eager to learn ...