8 of 8 Contract MLflow Jobs in the UK

pipelines Containerization (Docker, Kubernetes desirable) Model packaging and REST APIs Cloud & Tools (Any combination) AWS/Azure/GCP analytics and ML services MLflow, Azure ML, SageMaker, Vertex AI Version control (Git) Domain & Soft Skills Strong analytical and problem solving skills Ability to explain complex data science concepts in simple ...

experience with core GenAI frameworks (e.g., LangChain, LlamaIndex) and Agentic AI frameworks (e.g., AutoGen, CrewAI, LangGraph). Proficiency in MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes). Strong working knowledge and practical deployment experience on major cloud platforms (AWS, Azure, GCP), including their AI/ML services. Strong foundation ...

Proficiency in Python and common ML frameworks such as PyTorch, TensorFlow, or scikit-learn * Exposure to ML/MLOps tooling such as SageMaker, MLflow, or TFServing * Experience with Spark, Databricks, CI/CD tools, and streaming or orchestration systems like Kafka or Airflow How to Apply If you are interested ...

from stakeholder requirements through to algorithm hardening, edge-case handling, and value measurement Working with orchestration frameworks (Dagster/Airflow), experiment tracking (MLflow), and containerised infrastructure (Docker/ECS) Collaborating closely with business stakeholders and contributing to roadmap and feature prioritisation What We're Looking For Strong operational research ...

solve real-life problems and visualise the outcomes (e.g. seaborn) Proficient in working with cloud platforms (AWS preferred), code versioning (Git), experiment tracking (e.g. MLflow) Experience with cloud-based ML tools (e.g. SageMaker), data and model versioning (e.g. DVC), CI/CD (e.g. GitHub Actions), workflow orchestration (e.g. Airflow/ ...

Experience: 8-12+ years of experience in data/AI engineering or cloud architecture roles. Strong expertise with Databricks (Delta Lake, Unity Catalog, MLflow, Workflows). Deep understanding of AWS cloud architecture and services relevant to data/AI workloads. Hands-on experience designing large-scale distributed data systems ...

robust, maintainable, and scalable. Required Skills Programming: Advanced proficiency in Python. ML Engineering & MLOps: Hands-on experience with widely used ML tooling (e.g., MLflow, Airflow, Docker, Kubernetes). CI/CD & DevOps: Familiarity with CI/CD workflows and automation tools (e.g., GitLab, Jenkins) for streamlined deployments. Data Engineering Fundamentals ...

technical fluency across modern data and AI stacks including cloud-native architectures (Azure, AWS), data platforms (Databricks, Snowflake, Microsoft Fabric), ML/AI tools (MLflow, LLMs, RAG pipelines, vector stores) and analytics technologies (Power BI, Tableau) Experience reviewing end-to-end data programmes and defining future-state delivery models ...