1 to 25 of 66 scikit-learn Jobs in London

years) as a Machine Learning Engineer , Data Scientist , or similar role. Strong programming skills in Python (experience with libraries such as TensorFlow, PyTorch, scikit-learn, pandas, NumPy). Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools ...

Cortex) Understanding of natural language processing, computer vision, and recommender systems Strong programming skills in Python, SQL and proficiency with ML libraries (scikit‐learn, pandas, NumPy, XGBoost, LightGBM) Strong analytical and problem‐solving mindset with attention to detail Ability to work independently and drive projects from ambiguous requirements ...

transferable Proven experience as a Machine Learning Engineer within central government or regulated environments Strong programming skills in Python (e.g. Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch) Experience building and deploying ML models into production environments Strong knowledge of cloud platforms, particularly: Azure (ML Studio, Azure ML, Data Factory ...

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 ...

GenAI: Experience with LLM APIs and Context Engineering (constructing prompts, managing context windows, evaluating behaviour). Engineering & Stack: Python: Expert level (Pandas, NumPy, Scikit-Learn). Data Engineering: Strong SQL skills and experience building data pipelines. Experience: Education: Degree in a quantitative field (Statistics, Mathematics, Computer Science, etc. ...

/ML Requirements Basic to intermediate understanding of Machine Learning/Deep Learning concepts Experience using frameworks like TensorFlow/PyTorch/scikit-learn Ability to integrate pretrained models into Back End systems Familiarity with model deployment tools (eg, Docker, APIs, model serving) Preferred Qualifications Competitive programming experience ...

leading ML/AI technical initiatives across multiple teams Strong experience with cloud platforms (AWS, Azure, GCP) Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality management ...

leading ML/AI technical initiatives across multiple teamsStrong experience with cloud platforms (AWS, Azure, GCP)Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG)Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality management ...

degree in Computer Science, Mathematics, Statistics or a similar quantitative discipline Are proficient with Python, including open‐source data libraries (e.g., Pandas, Numpy, Scikit‐learn) Have experience productionising machine learning models and/or AI solutions Are an expert in one of predictive modelling, classification, regression, optimisation ...

experience delivering AI/ML projects end-to-end in production environments Strong Python skills with hands-on use of ML libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Solid understanding of machine learning fundamentals and performance evaluation techniques Experience working in cloud platforms ...

systems LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar frameworks RAG pipelines and vector databases AI agents and multi-agent orchestration Python, PyTorch, TensorFlow, Scikit-learn Cloud AI platforms such as AWS, Azure, or GCP Production deployment, MLOps, and scalable AI infrastructure API integration and workflow automation Bonus Points ...

multithreading) Expertise in RESTful API design, OpenAPI/Swagger documentation and API lifecycle best practices Hands-on experience with ML libraries: PyTorch, PySpark, scikit-learn, Hugging Face Transformers Proficiency in AI tooling: Azure ML, Databricks, MLflow, LangChain, LangGraph Proven experience with Git, unit testing, containerisation and agile methodologies ...

production and supporting them post-deployment.Strong Python programming skills, including object-oriented design and proficiency with key ML libraries (e.g., PyTorch, TensorFlow, Scikit-Learn).Solid understanding of probability and statistical modeling to support robust model development and interpretation.Experience with cloud platforms (especially Azure and/ ...

experience delivering advanced AI/ML solutions in industry or engineering environments. Strong expertise in Python and AI/ML libraries: PyTorch, TensorFlow, Scikit‐Learn, Keras, NumPy, Pandas, JAX, XGBoost, PyTorch Geometric, OpenCV, Transformers, LangChain, Pinecone . Proven hands‐on experience deploying models in production and building scalable ...

Strong commercial experience developing machine learning solutions in Python Solid understanding of the Python ML ecosystem including libraries such as NumPy, pandas, and scikit learn, with exposure to PyTorch or TensorFlow Experience building and deploying containerised services and APIs Working knowledge of SQL and data driven application development ...

understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining ...

real-world large data sets.Strong knowledge of hands-on practice in Python. Familiarity with popular machine learning libraries and frameworks such as scikit-learn, Hugging Face, PyTorch and TensorFlow. Experience with MLFlow, AWS SageMaker and Bedrock is preferred.Good written and oral communication skills, including the ability to communicate ...

customer-facing products Experience in travel, transport, marketplaces, or similarly complex digital platforms Our technology stack Python and associated ML/DS libraries (scikit-learn, NumPy, LightGBM, Pandas, LangChain/LangGraph, TensorFlow, etc.) PySpark AWS cloud infrastructure: EMR, ECS, Athena, etc MLOps/DevOps: Terraform, Docker, Airflow, MLFlow ...

track record delivering impactful ML/AI solutions in production. Deep expertise in Python and modern AI/ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn, NumPy, Pandas). Hands-on experience with GenAI, agentic AI, and automated testing for AI systems. Curiosity and creativity to challenge assumptions ...

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 ...

REST & GraphQL APIs Cloud & Infra: AWS (ECS, S3, Lambda), Docker, Cloudformation, Pulumi, CI/CD with GitHub Actions ML/AI: PyTorch, TensorFlow, scikit‐learn, MLflow for experiment tracking, Zenml for ML pipelines Data: PostgreSQL, DynamoDB, data pipelines with Zenml (We’re open to evolving the stack ...

computer vision projects Knowledge of AWS, Azure, or GCP Familiarity with Docker, APIs, or Git workflowsFamiliarity with frameworks such as PyTorch, TensorFlow, or Scikit-learn Internship, university project, or personal portfolio related to AI/ML What’s on Offer Competitive graduate salary package Company stock options/ ...

Scientist with production ML exposure Strong understanding of ML algorithms, model development, and deployment Experience with Python and ML frameworks (e.g. TensorFlow, PyTorch, scikit-learn) Familiarity with data pipelines and cloud or on-prem environments Understanding of MLOps principles Ability to work in secure or regulated environments Eligibility ...

/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 ...

lead by example technically, including: Applied ML on time-series/IoT/sensor/energy/building data Python (NumPy, pandas, scikit-learn, etc.) Productionisation of models into scalable workflows MLOps practices (e.g. MLflow, Airflow/Prefect, Docker) Building reproducible, well-tested data science pipelines Working with ...