7 of 7 Remote/Hybrid Jupyter Jobs

engaging with non-technical stakeholders to scope, design and build an appropriate ML solution. Proficient with Python data science stack, e.g., pandas, scikit-learn, Jupyter etc., and version control, e.g., Git. Exposure to LLMOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI etc. Knowledge ...

working with non-technical stakeholders to scope, design and deliver effective ML solutions. Proficient with the Python data science stack (pandas, scikit-learn, Jupyter, etc.) and version control tools like Git. Exposure to LLMOps, model monitoring, CI/CD and related technologies (Docker, MLflow, Kubernetes, FastAPI, etc.). Knowledge ...

support from more experienced colleagues. Some experience presenting technical findings to non-technical stakeholders. Proficient with the Python data science stack (pandas, scikit-learn, Jupyter, etc.) and version control tools like Git. Any exposure to LLMOps, model monitoring, CI/CD and related technologies (Docker, MLflow, Kubernetes, FastAPI, etc.). ...

into cloud and edge environments, and own the infrastructure that keeps them secure, scalable, and cost-efficient. You will be as comfortable in a Jupyter Notebook as you are in a Terraform config, with the ability to turn research ideas into production systems that run reliably in constrained environments. ...

colleagues in BI tools. Experience consolidating and migrating reports/dashboards from legacy systems. Knowledge of Oracle databases (desirable). Familiarity with Python and Jupyter notebooks (beneficial). Strong analytical and problem-solving skills, with attention to detail. Excellent communication skills to bridge technical solutions with business needs. Ability ...

technical stakeholders. Additional experience that would be helpful includes experience with Python or Rust backends, especially for scientific computing, and/or knowledge of Jupyter, WebAssembly, or scientific data formats (HDF5, NetCDF, FITS). A background in data dashboards, simulation visualisation, or instrument control interfaces would also be beneficial. Benefits ...

market view along with, next steps, and architectural patterns. HPC Tools, Runtimes & Ecosystem Integration Have a good understanding of Slurm scheduling, MPI job patterns, JupyterHub/JupyterLab for data-science workflows, GPU scheduling tools such as Run:AI, and SDLC practices tailored to research/HPC environments. Essential Skills & Experience ...