26 to 36 of 36 MLflow Jobs in the UK

Processing (NLP) and Computer Vision techniques Strong understanding of probability concepts and the machine learning lifecycle Experience with workflow and pipelining frameworks (e.g., Kubeflow, MLFlow, Argo) Awareness and application of Ethical AI principles This role offers a unique opportunity to work on cutting-edge projects, expand your expertise, and contribute ...

test splits are dangerous in time series and what to do about it. MLOps & Productionisation. Experience taking models from notebook to production: experiment tracking (MLflow, W&B), model versioning, feature stores, drift detection, and retraining triggers. You can build a model that doesn't just work once - it works reliably ...

Do you enjoy building infrastructure that powers complex engineering environments? Are you the type of engineer who loves improving performance, reliability and scalability across distributed systems? Looking for a role where your platform work directly ...

earth team What they're looking for: Solid experience with Databricks (Azure or AWS) Good understanding of tools like Delta Lake, Unity Catalog, MLflow Strong SQL and Spark (Python or Scala) Experience working with data pipelines and modern data platforms A good grasp of data modelling, warehousing, and general data ...

similar ML frameworks. Experience handling large datasets and distributed processing with PySpark or similar is desirable . Experience of experimentation tools such as MLflow is a bonus. Comfort with deploying ML models into production environments. Familiarity with AWS or similar cloud vendor . A methodical, problem-solving mindset with high ...

similar ML frameworks. Experience handling large datasets and distributed processing with PySpark or similar is desirable . Experience of experimentation tools such as MLflow is a bonus. Comfort with deploying ML models into production environments. Familiarity with AWS or similar cloud vendor . A methodical, problem-solving mindset with high ...

have a good knowledge of modern software engineering best practices, microservices, TDD/DDD, common Design Patterns Experience with Databricks, PostgreSQL, Amazon RedShift or MLflow would be great but not essential What's in it for you: As a Python Software Engineer (Machine Learning AWS) you will earn a competitive ...

training frameworks (DDP, FSDP, DeepSpeed). Background in NLP tasks such as NER, semantic similarity, QA, or dialogue systems. Experience with experiment tracking platforms (MLflow, Weights & Biases). Exposure to agentic AI paradigms (ReAct, chain-of-thought reasoning, tool use). Prior experience in leading AI research labs or high ...

including Circadia’s clinical monitoring hardware, working with firmware and embedded engineering teams as needed. Manage model versioning, promotion, and rollback workflows through the MLflow model registry. Evaluate and implement strategies for safe model rollouts (e.g. shadow deployments, canary releases) as the platform matures. Experiment Tracking & Model Registry Maintain … improve the MLflow-based experiment tracking and model registry infrastructure. Establish conventions for experiment logging, artifact storage, model metadata, and lineage tracking. Enable ML engineers to move seamlessly from experimentation to production deployment with minimal friction. Data & Model Versioning Implement and maintain training data versioning and dataset management practices ...

turn ideas into impactful solutions. Optimize and deploy models with tools like TensorFlow Serving, TorchServe, ONNX, and TensorRT. Build and manage ML pipelines using MLflow, Kubeflow, and Azure ML Pipelines. Work with large-scale data using PySpark and integrate ML solutions into production environments. Monitor and improve model performance … LightGBM, CatBoost, TensorFlow, Keras, PyTorch). Familiarity with model deployment and serving tools (ONNX, TensorRT, TensorFlow Serving, TorchServe). Experience with ML lifecycle tools (MLflow, Kubeflow, Azure ML Pipelines). Knowledge of distributed data processing (PySpark) and software engineering principles (Git). A collaborative mindset and excellent problem-solving abilities. ...

This role is critical to ensuring models are robust, reproducible and production-ready. Key responsibilities: • Deploy, manage and monitor ML models in production • Own MLflow, experimentation tracking and reproducibility • Build scalable training and deployment pipelines • Implement CI/CD for ML workflows • Optimise AWS infrastructure for performance and cost • Ensure … monitoring of ML endpoints Key details: • Salary: £80,000–£110,000 + discretionary bonus • Working: Hybrid, 3 days per week in London • Stack: Python, MLflow, AWS (SageMaker), CDK, Docker • Visa: Cannot sponsor Interested? Please apply below. ...