1 to 25 of 171 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 ...

cost efficiency, performance and scalability against standard benchmarks.18. Stay ahead of developments in GenAI (e.g. LLMs, multimodal models), ML frameworks (e.g. PyTorch, TensorFlow, Scikit-learn), orchestration tools (e.g. LangChain, LangFuse), model hubs. Taking responsibility for your own continuous professional development.19. Fostering a culture of responsible innovation and continuous ...

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). 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).\ 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). 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 ...

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 ...

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 ...

applications in large scale production environments. Experience managing data science teams and couching team members Proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn). Hands-on experience with agentic frameworks (LangChain, CrewAI, AutoGen, LangGraph, ADK). Experience with generative models (transformers, GANs/VAEs; diffusion models ...

applications in large scale production environments. Experience managing data science teams and couching team members Proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn). Hands-on experience with agentic frameworks (LangChain, CrewAI, AutoGen, LangGraph, ADK). Experience with generative models (transformers, GANs/VAEs; diffusion models ...

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). 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).\ 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 ...

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

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

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 ...

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

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

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