14 of 14 scikit-learn Jobs in Central London

Scientists and AI Engineers. Key experience includes: Expert-level Python development. Strong experience with core data science and machine learning libraries such as scikit-learn, pandas, PyTorch and/or TensorFlow . Practical experience with Databricks , including MLflow and Spark-based data processing. Hands-on knowledge of Generative ...

work on projects independently and own deliverables. Strong proficiency in Python for data manipulation, analysis, visualisation and data science (e.g., Pandas, NumPy, Scikit-learn). Proficiency in data querying languages (e.g., SQL). Solid understanding of software engineering best practices (version control, unit testing, code review, etc.). ...

from concept through to production. Strong technical knowledge, including expert‐level Python proficiency and experience with core data science and ML libraries (e.g., scikit‐learn, pandas, PyTorch or TensorFlow). Practical experience with Databricks, including MLflow for experiment tracking and model management, and Spark‐based data processing. Familiarity ...

Looking For: Essential Skills & Experience Proven experience solving complex, real-world problems using data science and analytics Strong Python skills (pandas, numpy, scikit-learn) with a solid grounding in probability and statistics Deep understanding of machine learning methods and their practical application Experience delivering multiple ...

into reliable, scalable systems. Essential experience includes: Commercial experience developing and deploying machine learning models in Python Proficiency with ML frameworks such as scikit-learn, XGBoost, PyTorch or TensorFlow Strong experience delivering ML solutions using AWS services (e.g. SageMaker, Lambda, S3) Expertise in experiment design, including hypothesis formulation ...

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 ...

experience 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, semanticsearchand knowledge graphs. Actively contributes to open-source AI projects, researchpublicationsand industry events ...

impact. Your Skills & Experience Strong experience deploying machine learning models into production. Advanced Python skills and experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch. Experience building and maintaining MLOps pipelines and CI/CD workflows. Strong knowledge of AWS, Azure, or GCP. Experience with ...

such as NLP, computer vision, audio, graphs, time-series or tabular data Strong Python skills and experience with common libraries (e.g. pandas, NumPy, scikit-learn, PyTorch, Transformers, statsmodels, PyMC) Understanding of software engineering and ML best practices, including version control, packaging and model deployment Experience training and deploying ...

able to write clean, production-ready code. Strong AI/ML fundamentals, including statistics, probability, linear algebra, and model evaluation. Experience with scikit-learn and either PyTorch or TensorFlow. Practical DevOps mindset: testing, CI/CD, reproducibility, code quality, and operational awareness. Excellent written and verbal communication; able ...

around you. Requirements Essential Expert Python, with deep hands-on PyTorch experience (TensorFlow also welcome) and the surrounding ecosystem: Hugging Face Transformers, timm, scikit-learn, NumPy, pandas, OpenCV. Production experience on AWS, specifically Amazon SageMaker: training and processing jobs, pipelines, model registry, endpoints. Practical MLOps: experiment tracking ...

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 ...

etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.) < Strong knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib) Strong software development skills (Python is the preferred language) Proven experience in deploying ML/AI services suing Kubernetes & KubeFlow Strong management ...

Scope and co-develop production-level data science projects with our customers across different industries and use cases Help users discover and master the Dataiku platform via user trainings, office hours, and ongoing consultative support ...