1 to 25 of 36 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 ...

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 ...

efficient deployments using Docker, Kubernetes (AKS/EKS/GKE), and Terraform/Bicep. Lead enterprise MLOps capabilities using Azure ML, SageMaker, Vertex AI, MLflow, and Kubeflow, integrated with CI/CD (GitHub Actions, Azure DevOps, Jenkins, Argo CD). Oversee observability and monitoring using Prometheus, Grafana, ELK/ ...

statistical evaluation Proven track record transitioning models from experimentation to production with appropriate governance and quality controls Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, Data Version Control) Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures It Would Be Great If You Also ...

FAISS, Milvus) Knowledge graphs and semantic search Data engineering pipelines MLOps & Deployment CI/CD for ML, model monitoring, versioning Kubernetes, Docker, serverless architectures MLflow, Kubeflow, SageMaker or similar Cloud & Architecture Azure AI, AWS AI/Bedrock, Google Vertex AI API-led architectures and microservices Security, governance, and responsible ...

pandas, scikit-learn, Jupyter etc., and version control, e.g., Git. Exposure to LLMOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI etc. Knowledge of Langchain, huggingface and LLM offerings by 3rd party vendors. Knowledge of OO programming and software design, i.e., SOLID principles. Knowledge ...

methodologies . Experience building production-grade AI systems using Python and ML frameworks (PyTorch, TensorFlow). Knowledge of MLOps/LLMOps practices and tooling (MLflow, Kubeflow, Docker, Kubernetes). Experience delivering AI solutions on AWS, Azure or GCP Experience leading or mentoring teams of AI engineers or data scientists. Robert ...

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 ...

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 ...

XGBoost, LightGBM, or CatBoost. Experience with model deployment tools (e.g., ONNX, TensorRT, TensorFlow Serving, TorchServe). Familiarity with ML lifecycle tools such as MLflow, Kubeflow, or Azure ML Pipelines. Experience working with distributed data processing (e.g., PySpark) and SQL. Understanding of software engineering best practices, including version control (Git). ...

scalable, maintainable, and production-ready AI systems. Proficiency in Python with AI/ML frameworks (PyTorch, TensorFlow). Experience with MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes). Deep proficiency in Python and extensive experience with relevant AI/ML/NLP libraries (e.g., Hugging Face Transformers, spaCy, NLTK ...

frameworks like AutoGen, CrewAI or LangGraph . Experience building RAG architectures with vector databases (Pinecone, Weaviate, FAISS). Strong understanding of MLOps/LLMOps (MLflow, Kubeflow, Docker, Kubernetes). Experience deploying AI solutions on AWS, Azure or GCP . Solid software engineering and full-stack development experience in enterprise environments. ...

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 ...

teams and delivering enterprise-grade data solutions. Preferred Qualifications Databricks certifications (e.g., Databricks Certified Data Engineer Professional, Architect ). Experience building ML solutions using MLflow or integrating with cloud ML services. Experience in BFSI, Retail, Telecom, or Healthcare data environments. Experience with real-time data processing (Kafka, EventHub, Kinesis). ...

learn, XGBoost, PyTorch, or TensorFlow Strong experience with cloud-based ML deployment (e.g., AWS SageMaker, Lambda, S3) Knowledge of MLOps/LLMOps tooling (e.g., MLflow, Weights & Biases, Data Version Control) Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures Ability to absorb complex scientific and technical concepts ...

deploying complex data solutions on the Microsoft Azure platform Experience collaborating with a range of stakeholders to structure data for downstream consumption (e.g. MLflow, Power BI semantic models) Infrastructure-as-code experience with Terraform for Azure resource provisioning Desirable Technical Skills Familiarity with streaming data architectures (Spark Structured Streaming) Knowledge ...

stack (pandas, scikit-learn, Jupyter, etc.) and version control tools like Git. Exposure to LLMOps, model monitoring, CI/CD and related technologies (Docker, MLflow, Kubernetes, FastAPI, etc.). Knowledge and working experience of AGILE methodologies. At Ageas we offer a wide range of benefits to support you and your ...

only. KEY SKILLS AI, Python, Machine Learning, Software Engineering, Data, APIs, Cloud, Agile, Python, TensorFlow, PyTorch, Scikit-learn, XGBoost, NLTK, OpenAI, LangChain, Pandas, NumPy, MLflow, Kubeflow, Docker, Kubernetes, Azure Machine Learning, Google Vertex ...

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 ...

Strong experience in at least one - Azure, AWS Very Nice to Have: • Databricks certifications (Data Engineer Associate/Professional) • Experience with Feature Store/MLflow • Exposure to Databricks AI/Mosaic AI/Model Serving If you’re interested in building high-performance Databricks platforms at scale, send your ...

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 ...

Knowledge of SQL and/or NoSQL databases AI/Machine Learning Exposure to ML/AI workflows or data science tooling Experience with MLflow or model tracking systems Scientific/Data Applications Experience working with scientific or bioinformatics datasets Exposure to single-cell RNA-seq, DNA/RNA sequences ...