1 to 25 of 147 scikit-learn Jobs in the UK

Conversational AI development Model training, testing and evaluation Prompt Engineering and AI workflow optimisation Programming & Frameworks Strong Python development skills PyTorch TensorFlow Scikit-Learn LangChain LangGraph Hugging Face FastAPI REST APIs Data Technologies SQL NoSQL Databases Data Modelling ETL Development Data Pipeline Engineering Vector Databases such as Pinecone ...

mentor engineers and scientists, lead applied research initiatives What You'll Bring Technical Expertise: Strong Python skills with the ML stack: NumPy, pandas, scikit-learn Hands-on experience with at least one deep learning framework (PyTorch, TensorFlow, JAX) Solid grounding in core ML—supervised, unsupervised, evaluation, regularisation, statistics ...

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). \n \n\n \n \nExperience with data storage for AI, vector databases, semantic search, and knowledge graphs. ...

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).\ N\n\n\n\ NExperience with data storagefor AI, vector databases, semantic search, and knowledge graphs.\ N\n\n\n\ NContributions ...

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). \n \n\n \n \nExperience with data storage for AI, vector databases, semantic search, and knowledge graphs. ...

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). \n \n\n \n \nExperience with data storage for AI, vector databases, semantic search and knowledge graphs. ...

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).\ N\n\n\n\ NExperience with data storagefor AI, vector databases, semantic search, and knowledge graphs.\ N\n\n\n\ NContributions ...

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).\ N\n\n\n\ NExperience with data storagefor AI, vector databases, semantic search and knowledge graphs.\ N\n\n\n\ NActively ...

unstructured data, especially large-scale text or content datasets. Familiarity with common data science and machine learning tools such as Pandas, NumPy, SciPy, Scikit-learn, PyTorch, TensorFlow, or Matplotlib. The ability to translate complex and ambiguous requirements into practical, measurable, data-driven solutions, with strong analytical thinking, problem ...

production environments.\ N\n\nExperience managing data science teams and couching team members\ N\n\nProficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn).\ N\n\nHands-onexperience with agentic frameworks (LangChain, CrewAI, AutoGen, LangGraph, ADK).\ N\n\nExperience with generative models (transformers, GANs/ ...

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).\ N\n\n\n\ NExperience with data storagefor AI, vector databases, semantic search, and knowledge graphs.\ N\n\n\n\ NContributions ...

feature engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection. \n\n \n Practical knowledge of ML frameworks (e.g. scikit-learn, PyTorch, XGBoost) and cloud-native ML services (SageMaker, Azure ML, Vertex AI). \n\n Platform & Cloud Engineering: \n \n Architecture and delivery ...

expertise: feature engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection. \ N\n\nPractical knowledge of ML frameworks (e.G. scikit-learn, PyTorch, XGBoost) and cloud-native ML services (SageMaker, Azure ML, Vertex AI). \ N\nPlatform & Cloud Engineering: \ N\nArchitecture and delivery of scalable ...

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 ...

Professional experience in a data science, ML engineering, or applied data role. \n Strong Python programming skills, including hands-on experience with pandas, scikit-learn, and at least one ML or deep learning framework. \n Working knowledge of Bedrock and other AWS managed services. \n Demonstrable experience building ...

Professional experience in a data science, ML engineering, or applied data role. \n Strong Python programming skills, including hands-on experience with pandas, scikit-learn, and at least one ML or deep learning framework. \n Working knowledge of Bedrock and other AWS managed services. \n Demonstrable experience building ...

Economics.\ NProfessional experience in a data science, ML engineering, or applied data role.\ NStrong Python programming skills, including hands-on experience with pandas, scikit-learn, and at least one ML or deep learning framework.\ NWorking knowledge ofBedrock and other AWS managed services.\ NDemonstrable experience building and deploying ...

Economics.\ NProfessional experience in a data science, ML engineering, or applied data role.\ NStrong Python programming skills, including hands-on experience with pandas, scikit-learn, and at least one ML or deep learning framework.\ NWorking knowledge ofBedrock and other AWS managed services.\ NDemonstrable experience building and deploying ...

tool/function calling, agentic workflows), including evaluation and safety patterns. Expertise with machine learning frameworks and data science packages (e.g., PyTorch, TensorFlow, Scikit‐Learn, NumPy, Pandas, SciPy, statsmodels). Experience deploying to AWS (e.g., SageMaker, Bedrock) and operating production workloads with attention to cost, performance, security ...

Python and SQL, with experience in data manipulation, model development, and analytical workflows. Hands‐on experience with machine learning frameworks such as scikit‐learn, TensorFlow, PyTorch, or similar. Strong experience with cloud platforms (AWS, Azure, or GCP) and building cloud‐native systems. Experience with modern data platforms such ...

learning Exposure to machine learning models and corresponding statistics like K‐means, Bayesian, Clustering Strong technical skills with Python along with NumPy, Pandas, Scikit‐Learn Machine learning experience -> predictive and prescriptive modelling Data wrangling and data cleansing experience Strong analytical skills Any experience with Node.JS would be beneficial. ...

Agentic AI and reinforcement learning.* Strong proficiency in programming languages, particularly Python.* Expertise in AI/ML frameworks such as PyTorch/TensorFlow, Scikit-learn, Statsmodels, LangGraph and ADK.* Familiarity with cloud platforms (preferably Google Cloud Platform and Vertex AI).* Strong analytical, critical thinking, and complex problem ...

Solid understanding of Scrum practices and a strong Agile mindset. Advanced proficiency in Python and its key data and ML libraries (NumPy, PySpark, Scikit learn, TensorFlow/PyTorch) Working knowledge of generative AI models (e.g., ChatGPT, Claude), Databricks GenAI tooling (including embedding models), and modern data structures such ...

computer vision projects Knowledge of AWS, Azure, or GCP Familiarity with Docker, APIs, or Git workflowsFamiliarity with frameworks such as PyTorch, TensorFlow, or Scikit-learn Internship, university project, or personal portfolio related to AI/ML What’s on Offer Competitive graduate salary package Company stock options/ ...

track record delivering impactful ML/AI solutions in production. Deep expertise in Python and modern AI/ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn, NumPy, Pandas). Hands-on experience with GenAI, agentic AI, and automated testing for AI systems. Curiosity and creativity to challenge assumptions ...