1 to 25 of 64 Permanent scikit-learn Jobs in the UK excluding London

years of hands‐on experience developing and deploying machine learning or statistical models within a commercial environment. Advanced proficiency in Python (pandas, NumPy, scikit‐learn) and advanced SQL. Solid understanding of core ML algorithms (e.g. XGBoost, LightGBM, linear/logistic regression, clustering, time‐series forecasting). Practical familiarity ...

agents). Strong proficiency in Python for AI/ML development, including use of common ML and data libraries (e.g. TensorFlow/PyTorch, scikit-learn, pandas, NumPy). Proven experience integrating AI services with enterprise systems via APIs and event-driven architectures. Practical experience with LLMs, prompt engineering ...

customers. Machine Learning, predictive modelling and applied AI, developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large ...

customers. Machine Learning, predictive modelling and applied AI, developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large ...

Data Scientist, Hands-on experience deploying ML models to production, not just research-level familiarity, Strong proficiency in Python (NumPy, pandas, scikit-learn, matplotlib, pytorch), Understanding of Windows or Linux software development platforms Excellent command of English – both written and spoken (international client communication, presentations), Expertise ...

proofs of concept and customer workshops. Required Skills Strong Python development skills with experience using AI/ML frameworks such as PyTorch, TensorFlow, Scikit‐Learn and Hugging Face. Proven experience developing and deploying machine learning solutions, including deep learning, computer vision, NLP/LLMs or time‐series analytics. ...

proofs of concept and customer workshops. Required Skills Strong Python development skills with experience using AI/ML frameworks such as PyTorch, TensorFlow, Scikit‐Learn and Hugging Face. Proven experience developing and deploying machine learning solutions, including deep learning, computer vision, NLP/LLMs or time‐series analytics. ...

customers. Machine Learning, predictive modelling and applied AI, developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large ...

machine learning, or statistical modeling, Practical experience with ML model deployment (on cloud or on-premise), Solid programming skills in Python (NumPy, pandas, scikit-learn, matplotlib, PyTorch or TensorFlow), Understanding of Windows or Linux software development platforms Good understanding of statistics and data preparation, Working knowledge ...

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 ...

like Python for model development, experimentation, and integration with OpenAI API. Experience with machine learning frameworks, libraries, and APIs, such as TensorFlow, PyTorch, Scikit-learn, and OpenAI API. Experience with cloud computing platforms (e.g., AWS, Azure, or Google Cloud Platform), containerization technologies (e.g., Docker and Kubernetes), and microservices ...

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. Actively contributes to open-source AI projects, research ...

will have experience in many of the following: Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/ ...

foundational model systems and frameworks/best practices for building agents. Experience using Python and common data science libraries such as pandas, scikit-learn, NumPy and visualisation frameworks. Strong SQL skills with experience querying and transforming large datasets, ideally using platforms such as BigQuery, Snowflake, or similar ...

language processing (NLP) and its applications. Solid coding level in Python programming language, with experience in leveraging available libraries, like Tensorflow, Keras, Pytorch, Scikit-learn, or others, to dedicated projects. Working with other team members to productionize end-to-end AI/ML solutions. Engaging in research ...

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 ...

across multiple ML domains, including: Forecasting/Time-Series Modelling Regression Classification Gradient Boosting models (e.g. XGBoost, LightGBM) Strong Python skills (Pandas, NumPy, scikit-learn, PyTorch) Experience with model evaluation, performance monitoring, and accuracy metrics Version control (Git) Experience working with cloud environments (Azure preferred, AWS/ ...

broad familiarity with common algorithms and architectures. Strong Python (pandas, NumPy, etc.) and SQL skills Comfortable with the standard ML toolkit: Git, Docker, scikit-learn, PyTorch or TensorFlow, and ML pipelines. Hands-on experience with text data and relevant Natural Language Processing techniques. Solid experience with cloud technologies ...

Experience with Cloud AI services such as Azure ML, AWS SageMaker, GCP Vertex AI. Hands-on experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch. Practical knowledge of algorithms and techniques such as regression, decision trees, random forest, XGBoost, k-means, anomaly detection, and time ...

. Experience with Git, CI/CD or Agile practices (from university or projects). Familiarity with machine learning basics (e.g., scikit-learn) and an interest in applying predictive analytics to identify trends and quality risks. Awareness of quality and continuous improvement methodologies, such as Lean Six Sigma ...

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 ...

understanding of traditional machine learning alongside generative AI, with practical experience in supervised and unsupervised learning and algorithms/frameworks such as XGBoost, scikit-learn or equivalent. Experience implementing RAG architectures using embeddings, vector databases/search technologies and enterprise data sources, with an understanding of retrieval quality ...

understanding of traditional machine learning alongside generative AI, with practical experience in supervised and unsupervised learning and algorithms/frameworks such as XGBoost, scikit-learn or equivalent. Experience implementing RAG architectures using embeddings, vector databases/search technologies and enterprise data sources, with an understanding of retrieval quality ...

using AI tools and agents as a core part of how they build, test and ship Strong Python, plus PyTorch, scikit-learn or similar frameworks Hands-on LLM work: prompting, fine-tuning, grounding and guardrails Agentic systems at scale, including orchestration (LangChain/LangGraph), tracing and evals (Langfuse ...