101 to 125 of 221 scikit-learn Jobs in the UK

experiment with new approaches and still care about getting models into production properly. What you could be working across Python PyTorch, TensorFlow or scikit-learn LLMs, RAG, agents and evaluation ML research and rapid prototyping MLOps and production ML pipelines Model deployment, monitoring and lifecycle tooling AWS, Docker ...

solid understanding of machine learning and deep learning methods 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 ...

concepts, automated testing, continuous integration and continuous delivery, and production deployments. Commercial experience using key Python libraries for machine learning, such as Pandas, Scikit-learn and XGBoost. Proven development experience with cloud services, data stores and architectures, such as Vertex AI, BigQuery and Cloud Run. Hands-on experience ...

concepts, automated testing, continuous integration and continuous delivery, and production deployments. Commercial experience using key Python libraries for machine learning, such as Pandas, Scikit-learn and XGBoost. Proven development experience with cloud services, data stores and architectures, such as Vertex AI, BigQuery and Cloud Run. Hands-on experience ...

Share ideas with the wider team, learn from and contribute to the body of knowledge Key Skills Experience using Python (pandas, numpy, scikit-learn) and SQL Theoretical understanding of core ML techniques and statistical principles Strong numerical and analytical skills, comfortable working with large datasets Confident communicator ...

modelling Cyber security Network analytics Our technology Our technology stack continues to evolve, but you'll typically work with: Python SQL AWS PyTorch Scikit-learn XGBoost Docker GitHub Claude Code GitHub Copilot LLMs AI Agents Why Friend MTS? You’ll work on problems very few engineers ever encounter. ...

experience in translating technical methods to non-technical stakeholders Strong 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 ...

tests, and report what the results do and don’t show Strong Python skills and hands‐on experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, PyTorch or Keras Solid grounding in modern software engineering, infrastructure and data tooling, and an understanding of the MLOps challenges across ...

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 ...

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 ...

willingness to explore how it can enhance your day-to-day work. Technologies and Tools Python Machine learning frameworks (e.g. PyTorch, TensorFlow, scikit-learn) ML/MLOps tooling (e.g. SageMaker, MLflow, TFServing) Spark and Databricks AWS services (e.g. IAM, S3, Redis, ECS) CI/CD tooling and best ...

with an orchestration tool such as Dagster (or Airflow, Prefect, etc.). Hands-on experience with common ML libraries and frameworks, e.g. PyTorch, scikit-learn, and gradient-boosting libraries such as XGBoost or LightGBM. Clear evidence of practical experience defining and deploying containerised systems, i.e.: Implementing APIs ...

stakeholders. Who we're looking for: You understand the full machine learning lifecycle and have experience operationalising models built with frameworks like Scikit-learn, TensorFlow, or PyTorch. You possess strong Python skills and solid experience in software engineering best practices. You bring hands-on experience with cloud platforms ...

stakeholders. Who we’re looking for: You understand the full machine learning lifecycle and have experience operationalising models built with frameworks like Scikit-learn, TensorFlow, or PyTorch. You possess strong Python skills and solid experience in software engineering best practices. You bring hands‐on experience with cloud platforms ...

ambiguous, fast‐moving environments Nice to have LLM applications for agentic solutions Graph modeling Personalization: propensity/uplift modeling, bandits, causal inference Libraries: scikit‐learn, XGBoost, LightGBM, CatBoost, CausalML, Keras, DoWhy Experience with dbt, Airflow, Looker or Metabase, AWS services such as S3 and Lambda Experience in designing ...

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 ...

MLOps and production deployment AI evaluation, testing and observability AI governance, model risk and engineering controls ML frameworks such as PyTorch, TensorFlow or Scikit‐learn Experience operating in complex, regulated or high‐risk environments would be particularly valuable. More important than any individual technology is the ability ...

stakeholders. Who we’re looking for: You understand the full machine learning lifecycle and have experience operationalising models built with frameworks like Scikit‐learn, TensorFlow, or PyTorch. You possess strong Python skills and solid experience in software engineering best practices. You bring hands‐on experience with cloud platforms ...

should have: Proficiency in Python: Ability to write functional, reproducible, and well documented code. Proficient with typical data scientist modules (pandas, numpy, matplotlib, scikit-learn). Strong Statistical knowledge: Good understanding of fundamental statistical concepts (e.g. bias, variance, R-squared). Good understanding of the theory and practice ...

deep technical expertise in particular topics and broad knowledge for solving complex problems; Have strong Python skills and practical experience operationalising models with Scikit-learn, TensorFlow, or PyTorch; Be an expert in at least one major Cloud Solution Provider, such as Azure, GCP, or AWS; Have experience leading ...

/DL/NLP/LLM systems in production environments.* Proficiency in Python and modern AI frameworks and tools (e.g. PyTorch, Transformers, Scikit-learn, OpenAI Codex, Claude Code).* Experience with data engineering, APIs, distributed systems, and cloud platforms (Azure/AWS/GCP).* Experience working with ...

Prefect etc Experience optimising dataframe code, e.g. in Pandas or ideally Polars Experience of machine learning techniques and related libraries and frameworks e.g. scikit-learn, Pytorch, Tensorflow etc Experience in scientific computing with other languages & frameworks Participation in the uncapped company bonus scheme, typically 15-25% of salary ...

with hands-on experience in data analysis and writing production-quality code. Extensive experience with machine learning and data analysis toolkits (e.g., NumPy, Scikit-Learn, Pandas). Ability to effectively leverage Generative AI tools to enhance productivity, analysis, and problem-solving in day-to-day work. Strong written ...

Understanding of statistics and data analysis Programming experience in Python (preferred) or similar languages Familiarity with AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) Knowledge of data structures, algorithms, and software development practices Experience with version control (e.g., Git) and collaborative development Experience in using computing environments ...

professional with a portfolio of innovative or academic projects. Technical Skills: Exposure to or experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Understanding of API development and integration. Familiarity with cloud platforms (e.g., AWS, Azure, or GCP) is a plus. Interest in RPA (Robotic ...