1 to 25 of 125 Permanent scikit-learn Jobs in the UK

technical processes. Required Skills & Qualifications Classic Machine learning (Regression, predictive Analysis, Classification, Clustering) Machine learning Model Optimisation Strong proficiency in Python (NumPy, Pandas, Scikit-learn). Hands-on experience with Deep Learning frameworks: TensorFlow, PyTorch, or Keras. Experience in Natural Language Processing (NLP) and/or Computer Vision. ...

automation scripts with proper logging, testing (pytest), and documentation. AI & Machine Learning Frameworks - Deep expertise in AI/ML frameworks including TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers. Experience building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model evaluation ...

setting. Education: Relevant Software Engineering/Computer Science degree. Technical Skills Programming Languages: Python, Java, C++, C#, TypeScript, JavaScript Machine Learning: TensorFlow, PyTorch, Scikit-learn GenAI/LLMs: OpenAI API, Hugging Face Transformers, LangChain, Langraph, RAG pipelines Data & Analytics: Pandas, NumPy, Spark, Databricks, Hadoop, Vector Databases, Snowflake Model ...

experience Strong SQL and experience working with large datasets Hands-on cloud experience (Azure, AWS or Snowflake) Expertise in machine learning frameworks (eg scikit-learn, XGBoost, PyTorch, TensorFlow) Strong knowledge of Generative AI, LLMs, RAG, embeddings and evaluation techniques MLOps experience (CI/CD, MLflow, containerisation, monitoring ...

production-grade analytical solutions. Hands-on experience with cloud platforms (Azure, AWS and/or Snowflake). Expertise in modern machine learning frameworks (scikit-learn, XGBoost, PyTorch, TensorFlow). Demonstrable experience delivering end-to-end ML and GenAI solutions (including RAG, LLMs, embeddings and vector databases). Strong ...

will collaborate with cross-functional teams to identify trends, patterns, and insights from large, complex datasets. Requirements Fluent Python, Pandas, Numpy, Matplotlib & Scikit-Learn 5+ consecutive years living in the UK Bachelor's or above in a STEM field (e.g., Maths, Physics, Data Science, Statistics, Computer Science) Ability ...

experience with LLMs, generative AI, NLP, or advanced modelling techniques. Proficiency in Python, SQL and modern data science libraries (e.g., PyTorch, TensorFlow, scikit-learn, HuggingFace). Experience mentoring or managing data scientists. Confident working in Agile environments with Git/version control. Strong communication skills, especially with ...

contribute to our internal library of proprietary tools and frameworks. Technical Profile Expert Programming: Mastery of Python and its ecosystem (Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow). Experience writing production-ready, modular, and well-tested code. Advanced Modeling: Deep theoretical and practical knowledge of Machine Learning. ...

GenAI: Experience with LLM APIs and Context Engineering (constructing prompts, managing context windows, evaluating behaviour). Engineering & Stack: Python: Expert level (Pandas, NumPy, Scikit-Learn). Data Engineering: Strong SQL skills and experience building data pipelines. Experience: Education: Degree in a quantitative field (Statistics, Mathematics, Computer Science, etc. ...

patterns, demand profiles, and commercial optimisation. Required Skills and Experience Technical Skills Proficiency in Python and associated data science libraries (NumPy, Pandas, SciPy, scikit‐learn, PyTorch/TensorFlow). Strong experience with time‐series modelling (ARIMA, Prophet, LSTMs or similar). Understanding of optimisation methods (linear, mixed‐integer ...

technical stakeholders What we’re looking for Essential experience Strong grounding in statistical modelling, experimentation and inference Advanced Python skills (NumPy, pandas, scikit-learn, PyTorch or TensorFlow) Experience building, deploying and optimising ML models in production Strong AWS experience (e.g. SageMaker, Lambda or similar services) Expert SQL skills ...

engaging with non-technical stakeholders to scope, design and build an appropriate ML solution. Proficient with Python data science stack, e.g., pandas, scikit-learn, Jupyter etc., and version control, e.g., Git. Exposure to LLMOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI ...

into production environments. Key skills and experience include: Strong programming skills in Python Experience with machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn Advanced knowledge of statistics, probability, and optimisation techniques Proven experience building, testing, tuning, and optimising machine learning models Comfortable working with large, complex ...

Strong knowledge of machine learning and/or optimisation techniques (Regression, Tree methods, Clustering, Linear/Mixed-Integer Programming, Heuristics) Strong Python experience (scikit-learn, pandas, numpy, optimisation libraries) Experience building production-ready ML or optimisation solutions Solid understanding of CI/CD , Git version control, and cloud ...

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 ...

Skilled at working with non-technical stakeholders to scope, design and deliver effective ML solutions. Proficient with the Python data science stack (pandas, scikit-learn, Jupyter, etc.) and version control tools like Git. Exposure to LLMOps, model monitoring, CI/CD and related technologies (Docker, MLflow, Kubernetes, FastAPI ...

closely related field Strong foundations in machine learning, algorithms, and statistics Experience with Python and common ML libraries (e.g. TensorFlow, PyTorch, scikit-learn) Understanding of software engineering fundamentals and version control (e.g. Git) Ability to communicate technical ideas clearly to both technical and non-technical stakeholders Right ...

systems, personalisation, or deep learning is desirable but not essential. Solid Python skills and experience with ML libraries such as pandas, numpy, scipy, scikit-learn, TensorFlow or PyTorch. Experience working across cloud environments (GCP, AWS, or Azure) and analytics platforms such as Dataiku. Good understanding of MLOps practices ...

Engineer will have the following skills and experience: Strong Python and SQL experience, ideally with Databricks Experience with ML and LLM tools (e.g., scikit learn, XGBoost, PyTorch, TensorFlow, RAG, APIs) Comfortable with data engineering basics and MLOps practices Experience working with cloud platforms such as Azure ...

solutions Implement experiment tracking and monitoring Collaborate with data scientists and engineers What We're Looking For: Proficiency in Python and ML frameworks (scikit-learn, PyTorch, TensorFlow) Hands-on experience with AWS ML services (SageMaker, Lambda) Familiarity with containerisation (Docker) and orchestration (Kubernetes/ECS) Knowledge of LLMOps ...

with support from more experienced colleagues. Some experience presenting technical findings to non-technical stakeholders. Proficient with the Python data science stack (pandas, scikit-learn, Jupyter, etc.) and version control tools like Git. Any exposure to LLMOps, model monitoring, CI/CD and related technologies (Docker, MLflow, Kubernetes ...

Fundamentals: You aren't limited to APIs. You have a background in training and evaluating models (TensorFlow/PyTorch/Keras/Scikit-learn) and know when a simple classifier is better than a generative model. Data Fluency: You understand how to build datasets from scratch (bootstrapping, crowdsourcing ...

Statistics, or related field Strong programming skills in Python (and optionally R, Java, or C++) Knowledge of ML frameworks like TensorFlow, PyTorch, or scikit-learn Eagerness to learn, curiosity, and a problem-solving mindset Nice to Have Cloud experience (AWS, GCP, Azure) Familiarity with MLOps tools (Docker ...

will not be considered) Experience with CI/CD pipelines for ML/DL models Proficiency in Python and common ML libraries (e.g. Scikit-learn, TensorFlow, PyTorch) Experience with container technologies (Docker, Kubernetes) Consultancy or client-facing experience preferred Strong communication and stakeholder management skills Qualifications IT/ ...

will not be considered) Experience with CI/CD pipelines for ML/DL models Proficiency in Python and common ML libraries (e.g. Scikit-learn, TensorFlow, PyTorch) Experience with container technologies (Docker, Kubernetes) Consultancy or client-facing experience preferred Strong communication and stakeholder management skills Qualifications IT/ ...