76 to 100 of 268 NumPy Jobs in England

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. ...

Science, Mathematics, Statistics or another STEM-related discipline. Desirable Skills Experience with cloud platforms such as AWS, Azure or GCP . Experience with Pandas, NumPy and Scikit-learn . Knowledge of data visualisation tools such as Power BI or Tableau. Experience with Git/version control. Exposure to Generative ...

analysis, computer vision, machine learning, or statistical modeling, Practical experience with ML model deployment (on cloud or on-premise), Solid programming skills in Python (NumPy, pandas, scikit-learn, matplotlib, PyTorch or TensorFlow), Understanding of Windows or Linux software development platforms Good understanding of statistics and data preparation, Working knowledge ...

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 and model versioning with ...

working with Parquet, Hive-partitioned datasets, and SQL against large tables (Athena/Presto). Solid working knowledge of the PyData stack — pandas and NumPy for data manipulation, Jupyter for experimentation, matplotlib/Seaborn for visualisation — and experience troubleshooting data-quality issues. Testing discipline with PyTest and a commitment ...

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 ...

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 ...

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 ...

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 and model versioning with ...

SaaS platform. Any other ad hoc duties that may be required from time to time Technical Requirements: Proven experience with Python, especially Pandas and NumPy Mastery of SQL and PostgreSQL: schema design, complex queries, indexing and performance optimisation, beyond basic querying Experience with pipeline orchestration and scheduling Proven ability ...

approach. Ability to 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. ...

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 and model versioning with ...

between technical developers and business teams, showcasing strong leadership, creativity, and ethical problem‐solving. Technical Expertise & Tools Python: Advanced, production‐grade proficiency (Pandas, NumPy, FastAPI/Flask) with an absolute focus on writing clean, modular, and highly testable code. SQL: Expert querying, database design, partitioning, and optimization strategies for large ...

translate business problems into measurable analytical outcomes. Experience taking models from development into production environments. Technical SkillsPython 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. ...

between technical developers and business teams, showcasing strong leadership, creativity, and ethical problem-solving. Technical Expertise & Tools : Python: Advanced, production-grade proficiency (Pandas, NumPy, FastAPI/Flask) with an absolute focus on writing clean, modular, and highly testable code. SQL: Expert querying, database design, partitioning, and optimization strategies for large ...

between technical developers and business teams, showcasing strong leadership, creativity, and ethical problem-solving. Technical Expertise & Tools : Python: Advanced, production-grade proficiency (Pandas, NumPy, FastAPI/Flask) with an absolute focus on writing clean, modular, and highly testable code. SQL: Expert querying, database design, partitioning, and optimization strategies for large ...

between technical developers and business teams, showcasing strong leadership, creativity, and ethical problem-solving. Technical Expertise & Tools : Python: Advanced, production-grade proficiency (Pandas, NumPy, FastAPI/Flask) with an absolute focus on writing clean, modular, and highly testable code. SQL: Expert querying, database design, partitioning, and optimization strategies for large ...

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 ...

review as standard practice Models you've personally taken into production and supported in life Machine learning across the usual toolkit: scikit-learn, pandas, NumPy, statsmodels or similar MLOps and CI/CD in practice. Pipeline orchestration, model versioning, automated deployment, monitoring and retraining Cloud based ML delivery, ideally Azure ...

Your Skills and Experience 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 ...

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 ...

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 ...

cycle processes and tools: CI/CD, version control (git), testing frameworks, MLOps. Experience with data science Python libraries such as Scikit-learn, Pandas, NumPy, Pytorch etc. Comfortable working with Docker and containerised applications Experience using AWS or similar cloud computing platform Experience delivering machine learning solutions within regulated environments ...

training of AI/ML solutionsSkills required: Overall 8+ years of experience. 5+ Years of strong Python coding skills and python libraries (like NumPy, Pandas etc.) 3 Years of solid understanding of generative AI models (GANs, VAEs, LLMs) and their underlying principles Strong experience in using Neo4J, Mongo DB Experience ...