7 of 7 scikit-learn Jobs in the Thames Valley

Master’s degree from a Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A passion More ❯

discussions and implementing solutions defined by project leads. Desirable Experience Strong Python expertise. Experience with GNU/Linux environments. Familiarity with key data science and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, Hugging Face). Experience in natural language processing, tabular data analysis, or computer vision. SQL proficiency. Exposure to containerisation (Docker, Kubernetes) and cloud-native architectures. More ❯

or other relevant AI fields. Proven track record of designing, developing, and deploying AI systems in production environments. Proficient in Python and key ML libraries (e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers). Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks, MLflow, LangChain, LangGraph. Proven experience with modern engineering practices More ❯

setting. Strong experience using data wrangling tools (e.g. Pandas, NumPy, dplyr). Solid grasp of statistical modelling and machine learning, with hands-on use of libraries such as scikit-learn, xgboost, PyMC3, TensorFlow. Experience working with SQL and relational databases. Ability to explain model behaviour through visualisations and reports. Familiarity with Git and collaborative development workflows. Good written More ❯

experience. Proven experience designing and deploying MLOps pipelines (MLflow, Azure ML, Azure DevOps etc). Strong programming skills in Python and familiarity with common ML/AI libraries (scikit-learn, tensorflow, Keras etc.). Experience implementing machine learning and large language models (LLMs), encompassing deployment, monitoring, and retraining. Familiarity with software engineering guidelines: version control (e.g., Git), CI More ❯

algorithms, and frameworks . Proficiency in programming languages (Python, R, C/C++, Java) and secure coding practices. Hands-on experience with ML/LLM frameworks (TensorFlow, PyTorch, scikit-learn, etc.). Expertise in DevOps/CI/CD security and cloud-native architectures (containers, Kubernetes, Git). Strong knowledge of AI/ML-specific security vulnerabilities (adversarial More ❯

stratigraphy, sedimentology, or petroleum geology. Experience of working with subsurface datasets (e.g., wireline, seismic, biostratigraphy). Strong python programming skills and experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Excellent communication and teamwork skills in a collaborative R&D environment. AI/ML Implementation: Design and implement AI/ML algorithms to automate and enhance geological More ❯