7 of 7 Remote/Hybrid MLflow Jobs in Manchester

Science, Machine Learning, or related field Nice to Have Published research in top ML venues (NeurIPS, ICML, ACL, CVPR). Experience with MLOps tools: MLflow, Weights & Biases, DVC. Familiarity with distributed training frameworks (DeepSpeed, Horovod). Experience with LLM fine-tuning and prompt engineering. Contributions to open-source ML projects. ...

development sectors.Strong proficiency in Python (pandas, scikit-learn, PyTorch/TensorFlow) and SQL, with experience in geospatial and environmental data analysis.Experience with MLOps tools (MLflow, Docker, CI/CD pipelines) and cloud platforms (Azure preferred), ensuring scalable and reliable solutions.Proven ability to influence non-technical stakeholders and communicate complex concepts ...

working with software engineering practices such as version control, testing, code review and CI/CD.Working with MLOps or workflow tools such as MLflow, Kubeflow, Argo or equivalent frameworks.Scaling models or analytical services for enterprise or operational use.Applying statistical methods, model evaluation techniques and uncertainty analysis.Understanding responsible AI, including fairness ...

integration/fine-tuning (OpenAI, LLaMA, Cohere, etc.)Strong coding in Python and experience with frameworks/tools such as FastAPI, PyTorch/TensorFlow, MLflow;3-5+ years of experience in designing and developing scalable web applications using modern front-end frameworks such as React/TypeScript. Experience working ...

systems at scale, including model lifecycle security, data pipelines, and secure deployment. Strong hands‐on experience with machine learning stacks, such as PyTorch, TensorFlow, MLflow, Kubeflow, or equivalent managed platforms (e.g. Vertex AI, Azure ML). Solid understanding of cloud‐native and containerised architectures, including Kubernetes and serverless technologies. Experience ...

that our Data Scientists use (we don't expect applicants to have experience with all of these):Python and Databricks for Data Science, Spark, MLFlow and Airflow for ML Workflows, Google Cloud Platform for our analytics infrastructure, dbt and BigQuery for data modelling and warehousing.Discover more about our Analytics Community ...

systems at scale, including model lifecycle security, data pipelines, and secure deployment.Strong hands‐on experience with machine learning stacks, such as PyTorch, TensorFlow, MLflow, Kubeflow, or equivalent managed platforms (e.g. Vertex AI, Azure ML).Solid understanding of cloud‐native and containerised architectures, including Kubernetes and serverless technologies.Experience operating in complex ...