7 of 7 Permanent MLOps Jobs in the South West

members and providing technical leadership. Desirable Skills & Experience MSc or PhD with a strong research background. Experience developing and maintaining robust ML pipelines and MLOps practices. Familiarity with version control, containerisation and environment management tools, including Git and Docker. Experience working within Linux environments and using command-line tooling. Experience ...

internal stakeholders. Excellent coding practice using Python and associated ML packages (HuggingFace, TensorFlow, PyTorch), following best practices. Experience developing robust ML pipelines with MLOps tools for model training, monitoring and deployment. Experience of appropriate version control and environment management (such as venvs or Docker). Experience of writing technical project ...

internal stakeholders. Excellent coding practice using Python and associated ML packages (HuggingFace, TensorFlow, PyTorch), following best practices. Experience developing robust ML pipelines with MLOps tools for model training, monitoring and deployment. Experience of appropriate version control and environment management (such as venvs or Docker). Experience of writing technical project ...

Engineering or equivalent professional accreditation such as CEng. Experience with graph databases and advanced query languages (e.g., Knowledge of machine learning data pipelines and MLOps practices. Familiarity with data virtualisation and data mesh concepts. Experience with BI/visualisation tools (e.g., Tableau, Power BI, Looker, Elastic Stack). Knowledge ...

areas, and encourage anyone with the experience listed above to apply. We would particularly like to encourage applicants with experience in the following areas: MLOps: including tools like LangChain for application development and managing the ML lifecycle Data Engineering: including platforms like Databricks for data processing and analytics DevSecOps & DevOps ...

applying analytical techniques. Familiarity with Git and reproducible research practices. Desirable Experience Exposure to cloud platforms such as AWS, Azure, or GCP. Knowledge of MLOps practices and tooling. Experience in areas such as NLP, time series analysis, or computer vision. Comfortable presenting technical work and insights to stakeholders. Whats ...

hypothesis development, testing and evaluation Transition successful models from proof of concept into production environments Develop scalable ML pipelines using AWS cloud technologies Implement MLOps and LLMOps best practices for deployment, monitoring and governance Support feature engineering, model optimisation and performance monitoring Apply responsible AI principles, including model explainability … Python Experience with frameworks such as PyTorch, TensorFlow, Scikit-learn or XGBoost Knowledge of AWS cloud services including SageMaker, Lambda and S3 Experience with MLOps tools such as MLflow, Weights & Biases or Data Version Control Experience designing, testing and evaluating machine learning experiments Knowledge of Generative AI, LLMs, prompt engineering ...