51 to 75 of 247 scikit-learn Jobs in the UK

Senior-level experience in data science or a quantitative field Proficient programming skills (Python preferred); familiarity with core data science libraries (NumPy, Pandas, Scikit-Learn) Experience with deep learning tools (e.g. PyTorch, TensorFlow, or similar) Strong mathematical/statistical background Familiarity with a wide range of data science ...

Senior-level experience in data science or a quantitative field Proficient programming skills (Python preferred); familiarity with core data science libraries (NumPy, Pandas, Scikit-Learn) Experience with deep learning tools (e.g. PyTorch, TensorFlow, or similar) Strong mathematical/statistical background Familiarity with a wide range of data science ...

PyTorch, and Azure. Do you have? Experience developing AI/ML solutions using Python? Knowledge of frameworks such as PyTorch (preferred), TensorFlow, or Scikit-learn? Experience with NLP, deep learning, or computer vision? Familiarity with MLOps tools (Azure ML Pipelines, MLflow, Docker, Kubernetes)? Experience working with cloud platforms ...

Embeddings Transformers: BERT, ELMo OpenAI Models: GPT-3.5 Turbo, GPT-4o, GPT-3o Reasoning, text-embedding-ada-002 Libraries & Tools numpy, pandas, scipy, scikit-learn, tensorflow, keras, nltk, matplotlib, seaborn, plotly Programming Languages Python, R, C++, C#, Java, Node.js, HTML, SQL Agentic AI OpenAI Agents SDK, Model Context ...

talented ML Ops Engineer to join our growing teams. Key Responsibilities Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow ...

data scientist in industry or similar environment. Good knowledge of python, along with common machine learning and data analysis libraries (e.g. pandas, numpy, scikit-learn, pytorch, transformers, statsmodels, pymc). Ability to absorb complex new scientific concepts and quickly get up to speed on new areas ...

systems. Build, train, fine-tune, and evaluate AIML models for automation use cases. Develop Python-based data pipelines and algorithms using NLTK, NumPy, Scikit-learn, Pandas. Collaborate with cross-functional teams in an Agile setup (sprint planning, refinement, retrospectives). Integrate solutions with test automation frameworks ...

Experience with generative models (GANs, VAEs, Diffusion models) Programming & Tools : Expert-level Python programming Proficiency with ML frameworks (PyTorch, TensorFlow, JAX) Experience with scikit-learn, XGBoost, LightGBM Strong software engineering practices and clean code principles Data & Computing : Experience with big data technologies (Spark, Dask) SQL and NoSQL databases ...

embeddings and semantic search Collaborating with engineering, data and product teams What you'll need: Strong Python and experience with TensorFlow, PyTorch or scikit-learn Hands-on LLM work—prompt engineering, modern NLP techniques AWS experience: SageMaker, Bedrock, S3, Lambda, CloudWatch Understanding of deep learning, transformers and attention ...

experience delivering Data Science or Machine Learning solutions in a commercial setting. Strong programming skills in Python (preferred) or R, with experience using scikit-learn, pandas, PySpark or similar. Solid SQL skills and experience working with cloud environments (Azure advantageous). Hands-on experience with Databricks, model deployment ...

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/ ...

research techniques to real-world business problems Proficiency in Python (production-level) and SQL ; experience with modern ML/AI libraries such as scikit-learn, TensorFlow or PyTorch Familiarity with MLOps , model deployment and cloud platforms such as Databricks, AWS or Azure It would be great ...

/AI, preferably in energy, industrial automation, or smart infrastructure. · Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn, and programming in Python, R, MATLAB, or C++. · Experience deploying ML models in production using MLOps principles. · Familiarity with cloud platforms (AWS, Azure, Google Cloud ...

junior data scientists and help shape AI best practice Requirements Strong experience in AI, machine learning and statistics Python expertise (e.g. pandas, NumPy, scikit-learn, PyTorch, transformers) Experience deploying models and working with cloud platforms (AWS preferred) Ability to communicate complex technical concepts clearly Desirable AWS services (SageMaker ...

into simple, actionable insights What We’re Looking For 🚀 1–3 years’ experience in data science or analytics 🐍 Strong Python skills (pandas, numpy, scikit-learn) 🗄️ Solid SQL for data extraction and manipulation 📊 Experience with Tableau or Power BI is a bonus 🧠 Strong problem-solving and analytical thinking 🎤 Clear ...

into simple, actionable insights What We’re Looking For 🚀 1–3 years’ experience in data science or analytics 🐍 Strong Python skills (pandas, numpy, scikit-learn) 🗄️ Solid SQL for data extraction and manipulation 📊 Experience with Tableau or Power BI is a bonus 🧠 Strong problem-solving and analytical thinking 🎤 Clear ...

Level Published papers Good understanding of software engineering concepts Experience with machine learning Python frameworks such as PyTorch, Tensorflow and Scikit-Learn Data Science experience including working with large data sets Responsibilities for Machine Learning Research Engineer Join a team responsible for investigating the latest research in machine ...

Level Published papers Good understanding of software engineering concepts Experience with machine learning Python frameworks such as PyTorch, Tensorflow and Scikit-Learn Data Science experience including working with large data sets Responsibilities for Machine Learning Research Engineer: Join a team responsible for investigating the latest research in machine ...

Expertise: •Proven experience in data science leadership roles with team management. •Strong expertise in Azure Machine Learning, Python, and ML frameworks (TensorFlow, PyTorch, Scikit-learn). •Hands-on experience with MLOps, CI/CD pipelines, and model monitoring. •Knowledge of cloud architecture, data engineering, and security best practices. ...

Expertise: •Proven experience in data science leadership roles with team management. •Strong expertise in Azure Machine Learning, Python, and ML frameworks (TensorFlow, PyTorch, Scikit-learn). •Hands-on experience with MLOps, CI/CD pipelines, and model monitoring. •Knowledge of cloud architecture, data engineering, and security best practices. ...

Expertise: •Proven experience in data science leadership roles with team management. •Strong expertise in Azure Machine Learning, Python, and ML frameworks (TensorFlow, PyTorch, Scikit-learn). •Hands-on experience with MLOps, CI/CD pipelines, and model monitoring. •Knowledge of cloud architecture, data engineering, and security best practices. ...

data preparation. Significant experience leveraging SQL and Python for data querying and automation; familiarity with AI/ML libraries or APIs (e.g., OpenAI, scikit-learn, or similar) is preferred. Experience with visualization tools such as Tableau, Power BI, or AI-augmented BI tools (e.g., Tableau Pulse, Power ...

data preparation. Significant experience leveraging SQL and Python for data querying and automation; familiarity with AI/ML libraries or APIs (e.g., OpenAI, scikit-learn, or similar) is preferred. Experience with visualization tools such as Tableau, Power BI, or AI-augmented BI tools (e.g., Tableau Pulse, Power ...

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 ...

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 ...