1 to 25 of 117 scikit-learn Jobs in the UK excluding London

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). 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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Senior/Lead roles) Set standards, mentor scientists and lead cross-functional initiatives What You'll Bring Technical Expertise: Strong Python (pandas, scikit-learn, statsmodels) and/or R Solid statistics—inference, experimental design and causal methods Machine learning—supervised and unsupervised methods and rigorous evaluation Strong ...

solve real-world problems in industry or academia Strong Python programming skills and deep familiarity with the Python ecosystem (i.e. pandas, numpy, scikit-learn, pytorch, pip, pytest) Demonstrated ability to lead technical teams and initiatives with strong communication and stakeholder management skills Preferred qualifications, capabilities, and skills: Experience ...

modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), and advanced ML libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. Active contribution to open-source AI projects, research ...

modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), and advanced ML libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. Active contribution to open-source AI projects, research ...

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 VertexAI). Strong analytical, critical thinking, and complex problem‐solving ...

scale customer datasets into robust, auditable predictive models, supporting forecasting, risk analysis and commercial data products. Key skills & experience Strong Python (Pandas, NumPy, Scikit-learn) and SQL skills. Experience with Snowflake or similar cloud data platforms. Proven track record building predictive models in regulated financial services environments. Credit ...

with significant industry or research experience in the field Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals ...

product teams to transform raw data into robust, auditable, and commercially valuable solutions. Skills & Experience Technical Expertise Strong proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL . Hands-on experience with Snowflake or similar cloud-based data warehouse platforms. Experience using Git and reproducible development practices. Strong ...

using mathematical, ML and software techniques to solve industrial problems and deliver business impact. Modern Tech Stack: Advanced proficiency in Python (pandas, NumPy, scikit-learn) and SQL. Communication: Exceptional ability to explain complex technical concepts, algorithmic trade-offs, and probabilistic outputs to non-technical business partners. Nice ...

data and implementing data science processes. Experience in translating customer requirements intotechnical requirements and development objectives. Pythonexpertisecovering standard data sciencelibraries (NumPy, pandas, matplotlib, Scikit-learn,PyTorch, etc),web frameworks (Flask or FastAPI) and visualisation(Dash,Plotly,&Streamlit). Proficient inSQL. Working with unstructured data Building customer and stakeholder ...