7 of 7 MLflow Jobs in Central London

building simple data pipelines or transformation workflows is a plus. Exposure to ML Ops or production systems (nice to have) Familiarity with tools like MLflow, Weights & Biases, or cloud platforms (Azure, AWS, or GCP). Experience deploying models via APIs or lightweight services is a bonus, not a requirement. Software ...

Ollama advantageous). Strong grasp of CI/CD, testing, version control, secure coding, and modern engineering workflows. Exposure to MLOps tools such as MLflow, Kubeflow, or Azure ML. ...

Solid ETL, data processing, and feature engineering experience. Strong statistical and analytical capabilities. Experience in start-up or scale-up environments. Desirable MLOps tools (MLflow, Kubeflow, Sagemaker, etc.) Experience in PropTech or property data. Cloud experience (AWS/GCP/Azure). Docker/Kubernetes, CI/CD, and event ...

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 ...

Working model: On-site 4–5 days/week across UK client locations in England & Scotland (travel required) • Tech Stack: Python, MLflow, Databricks, Docker, Azure OpenAI, simulation frameworks • Clearance: British citizenship/Security Clearance eligibility required • Visa: This role cannot sponsor Interested? Please apply below. ...

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 ...

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. ...