1 to 25 of 152 NumPy Jobs in London

Physics, or related); Master's degree preferred. Professional software development experience, with deep expertise in Python and its data/engineering ecosystem (e.g., pandas, NumPy, FastAPI, orchestration tools). Proven track record of delivering production-grade automation, data pipelines, or testing frameworks in a complex enterprise environment; financial services experience ...

technical audiences, advocating for interpretability and audit best practices.Experience working with structured and unstructured datasets.Proficient in Python, leveraging key data science libraries (NumPy, Pandas, scikit-learn) and applying object-oriented programming principles to develop efficient, scalable solutionsHands-on experience experimenting with Generative AI (e.g. LangChain, Hugging Face, LlamaIndex).Experience working ...

Experience of cloud platforms (AWS, Azure, or GCP) Experience of containerisation (Docker) and orchestration (Kubernetes) Exposure to data engineering tools/libraries (e.g. Pandas, NumPy) or NLP libraries Knowledge of message queues/event-driven architecture (e.g. RabbitMQ, Kafka) Understanding of CI/CD tools (e.g. Jenkins, GitHub Actions, Azure ...

Judge, BERTScore, BLEU score, and hallucination detection.Provide mentorship and technical guidance to junior AI ScientistsSkillsStrong proficiency in Python and experience with frameworks such as NumPy, Pandas, Scikit-learn, and modern Generative AI libraries (e.g., LangChain, LlamaIndex, Azure AI Foundry).Hands-on experience with PyTorch, and leading LLM libraries such ...

What We’re 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 ...

your Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using ...

your Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using ...

your Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using ...

your Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using ...

your Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using ...

your Python skills by building a car price prediction app using Python and Streamlit. Step 6 - Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 - AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using ...

your Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using ...

experience, and a passion for building scalable, high-quality ML and data solutions in production environments. Essential Experience Strong programming skills in Python (Pandas, NumPy, etc.). Proficiency in SQL for data querying and transformation. Hands-on experience with Machine Learning techniques and frameworks (e.g., scikit-learn, TensorFlow, PyTorch). ...

experience, and a passion for building scalable, high-quality ML and data solutions in production environments. Essential Experience Strong programming skills in Python (Pandas, NumPy, etc.). Proficiency in SQL for data querying and transformation. Hands-on experience with Machine Learning techniques and frameworks (e.g., scikit-learn, TensorFlow, PyTorch). ...

engineering skills, with a track record of building and maintaining production‐quality systems. Expert‐level Python experience with numerical, statistical, or ML libraries (e.g. NumPy, pandas, PyTorch, JAX, TensorFlow). Deep understanding of statistical modelling, optimisation, or machine‐learning techniques. Experience building and operating backend systems and data pipelines ...

design and software engineering fundamentals: version control, code review, automated testing, dependency and environment management. Machine learning across the standard toolkit (scikit learn, pandas, NumPy, statsmodels or equivalents), with sound judgement about model selection, validation and the limits of what the data supports. MLOps and CI/CD in practice ...

large scale, high impact machine learning solutions from initial experimentation through to deployment. Strong knowledge of data science libraries such as Polars, Pandas, NumPy, Scikit-learn. Knowledge of MLOps tooling such as Weights & Biases, AirFlow, AWS SageMaker or Docker. Experience working with cloud platforms such as AWS, Azure or GCP. ...

Kubernetes for scalable production systemsFamiliarity with distributed computing frameworks (e.g., Spark, Dask), cloud platforms (e.g., AWS, Azure, GCP), and analytics libraries (e.g., pandas, numpy, matplotlib)Exposure to DevOps, DataOps, and MLOps concepts and best practicesExperience with core technologies such as Python, PySpark, SQL, Airflow, Databricks, Kedro, Dask/RAPIDS, Docker ...

professional setting (e.g., internship) is a plusAbility to write clean, maintainable, scalable, and robust code in PythonFamiliarity with analytics libraries (e.g., pandas, numpy, matplotlib), distributed computing frameworks (e.g., Spark, Dask), and cloud platforms (e.g., AWS, Azure, GCP)Basic understanding or exposure to containerization technologies such as Docker and Kubernetes would ...

production. You write production-grade code, not just notebooks.Strong Python and SQL (we use Snowflake). Comfortable with the scientific Python stack: Polars, Pandas, NumPy, SciPy, and scikit-learn. Experience developing and evaluating ML models on tabular data classification or regression tasks where evaluation matters as much as model choice. ...

translate business problems into measurable analytical outcomes.* Experience taking models from development into production environments.### Technical Skills* Python and associated data science ecosystem (Pandas, NumPy, Scikit-learn).* Machine learning techniques including classification, regression, clustering and anomaly detection.* Experience with Generative AI, LLMs, RAG architectures or agent-based AI solutions. ...

write production-grade code, not just notebooks. Strong Python and SQL (we use Snowflake). Comfortable with the scientific Python stack: Polars, Pandas, NumPy, SciPy, and scikit-learn. Experience developing and evaluating ML models on tabular data classification or regression tasks where evaluation matters as much as model choice. Think ...

engineering skills, with a track record of building and maintaining production‐quality systems. Expert‐level Python experience with numerical, statistical, or ML libraries (e.g. NumPy, pandas, PyTorch, JAX, TensorFlow). Deep understanding of statistical modelling, optimisation, or machine‐learning techniques. Experience building and operating backend systems and data pipelines ...

memory management, and interoperability protocols such as MCP Experience with machine learning frameworks and data science packages such as PyTorch, TensorFlow, scikit‐learn, NumPy, pandas, SciPy, and statsmodels Experience deploying to AWS, including services such as SageMaker and Bedrock, and operating production large language model and machine learning workloads with ...

loop review.Strong programming and data skills, including Python, SQL, and tools/libraries used in agentic development like langgraph, langchain, Pydantic models, NumPy, FastAPI/MCP, etc.Ability to work with APIs, JSON, MCPs, Git or version-controlled artifacts, and lightweight automation or prototyping workflows.Excellent written and verbal communication skills, with ...