1 to 25 of 90 scikit-learn Jobs in the UK

products. Key Skills & Experience: Experience in machine learning, data science, or applied AI roles. Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Strong understanding of statistics, ML algorithms, and model evaluation techniques. Experience working with cloud platforms (AWS, Azure ...

products. Key Skills & Experience: Experience in machine learning, data science, or applied AI roles. Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch).Strong understanding of statistics, ML algorithms, and model evaluation techniques. Experience working with cloud platforms (AWS, Azure, or GCP) and ML pipelines. ...

bids, proofs of concept and customer workshops. QualificationsRequired SkillsStrong 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. ...

supervised learning, unsupervised learning, statistical modelling, feature engineering, validation, model evaluation and optimisation. · Hands-on experience with Python-based machine learning libraries, especially Scikit-Learn and at least one of XGBoost, LightGBM, TensorFlow or PyTorch. · Experience developing models beyond exploratory analysis into reusable, documented and testable assets, ideally ...

Jira, GitHub, and GitLab. Hands-on experience building, deploying, and scaling AI/ML solutions using frameworks and platforms such as Scikit-learn, PyTorch, TensorFlow, Hugging Face, LangChain, Databricks, Spark, vector databases, cloud services (AWS/Azure), and MLOps tools including MLflow and Kubeflow. Proven ability to develop ...

business problems into measurable analytical outcomes. Experience taking models from development into production environments. Technical SkillsPython and associated data science ecosystem (Pandas, NumPy, Scikit-learn).Machine learning techniques including classification, regression, clustering and anomaly detection. Experience with Generative AI, LLMs, RAG architectures or agent-based AI solutions. ...

/LLMs, multimodal AI, self-supervised learning, reinforcement learning, time-series analytics or foundation models. Experience with AI frameworks and libraries: PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers; OpenCV for vision applications. Strong understanding of experimental design, statistical evaluation, benchmarking and model validation. Experiment tracking and reproducibility tools ...

bottlenecks to strategic AI solutions. Software/Data Engineering: Python proficiency, API design, SQL, data integration, and ML/AI libraries (PyTorch, TensorFlow, scikit-learn, XGBoost, Hugging Face Transformers).Agentic AI Systems: Hands-on experience with agentic AI setups including LLM orchestration, tool use/function calling ...

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 ...

leading ML/AI technical initiatives across multiple teams Strong experience with cloud platforms (AWS, Azure, GCP) Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality management ...

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/ ...

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/ ...

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/ ...

causal inference techniques (e.g., diff-in-diff, IV, matching) where randomization is impracticalFluency in Python and core data/ML libraries (pandas, NumPy, scikit-learn, PyTorch or TensorFlow), combined with solid software engineering practices (clean code, testing, version control, code review)Proficient with large-scale data: strong ...

science processes. · Experience in translating customer requirements into technical requirements and development objectives. · Python expertise covering standard data science libraries (NumPy, pandas, matplotlib, Scikit-learn, PyTorch, etc...), web frameworks (Flask or FastAPI) and visualisation (Dash, Plotly, & Streamlit). · Proficient in SQL. · Working with unstructured data · Building customer ...

appropriate. Experience designing evaluation frameworks for AI-generated or retrieval-based outputs. Data & EngineeringFamiliarity with machine learning frameworks such as PyTorch, TensorFlow, Scikit-learn, and Hugging Face. Experience with cloud platforms and modern development workflows, including Git and CI/CD.Understanding of MLOps practices, including experiment tracking, deployment ...

logical, curious approach to solving problems Willingness to learn quickly and take feedback Desirable experience: Familiarity with libraries such as pandas, NumPy, scikit-learn, PyTorch or TensorFlow Experience calling a large language model through an API, or building a simple prompt-based tool Exposure to cloud platforms ...

Desirable Experience Machine Learning model development and training. LLMs, transformers, RAG and Agentic AI. LangChain, LangGraph or similar AI orchestration frameworks. PyTorch, TensorFlow, Scikit-learn or Hugging Face. Vector databases, embeddings and model evaluation. NLP, Computer Vision or multimodal AI. Edge AI, AI safety, security or explainability. Experience ...

including probability, statistics, and common learning techniques. You understand the full machine learning lifecycle and have experience operationalising models built with frameworks like Scikit-learn, TensorFlow, or PyTorch. You're an excellent communicator, able to guide technical teams and confidently advise non-technical stakeholders. You thrive ...

define what 'good' means for a model, build the test set and measure it. Strong grounding in the ML stack, such as PyTorch, scikit-learn, Hugging Face and vector databases, alongside sound software engineering practice. Experience deploying and monitoring models on cloud infrastructure, ideally AWS, with ...

deployment. Key Skills Strong Python and SQL skills. Experience building and deploying ML models in production. Hands-on knowledge of machine learning frameworks (Scikit-learn, TensorFlow, PyTorch). Data engineering and pipeline development experience. Cloud experience (AWS, Azure, or GCP). Strong understanding of software engineering best practices. ...

Engage with senior stakeholders and contribute to business development initiatives. Provide thought leadership through industry engagement and innovation. Requirements Strong Python, SQL, Pandas, Scikit-Learn and Spark experience. Experience delivering real-world AI and machine learning systems. Understanding of statistics and machine learning methodologies. Experience with cloud platforms ...

least two of the following: Python, R, or Julia. Hands-on experience using data science and machine learning libraries such as Pandas, NumPy, Scikit-Learn, TensorFlow, PyTorch, Keras, or equivalent. Experience working with Next Generation Sequencing (NGS), OMICS datasets, or other large-scale biological data. Knowledge of variant ...

problemsProven experience in translating technical methods to non-technical stakeholdersStrong programming experience in Python and the relevant analytics libraries (e.g., pandas, numpy, matplotlib, scikit-learn, statsmodels, pymc, pytorch/tf/keras, langchain). R and C++ optional. Experience with version control (GitHub)ML experience with causality, Bayesian ...

series work Data and ML pipelines built for production, not demos Dashboards and tools that non-technical users can act on Python (Pandas, scikit-learn, PyTorch/TensorFlow), Spark and AWS Why it's worth a look Real operational deployment, not endless proofs of concept Direct contact with ...