26 to 50 of 137 MLflow Jobs in London

containerisation (Docker/Kubernetes). Strong background in data modelling, warehousing, and supporting analytical and ML workloads. Exposure to MLOps tools including MLFlow, kedro and Amazon Sagemaker. Development and maintenance of real time products like APIs using FastAPI/Flask. Operates autonomously with strong ownership and accountability. Strategic thinker ...

experience with Generative AI and LLM deployment patterns. A proven history of reducing cloud spend on large-scale AI clusters. Experience with tools like MLflow, Kubeflow, LangSmith, or Phoenix. Expertise in AWS/GCP/Azure cost tools, Kubecost, or Cloudability. Extensive background of Kubernetes (K8s), Docker, and service meshes. ...

Docker, Helm, KubeFlow, and service meshes (e.g., Istio). Hands-on experience with Terraform, Ansible, GitHub Actions, ArgoCD, or Jenkins. Experience with vLLM, Ray, MLflow, LangChain/LangSmith, DeepSpeed, or Hugging Face TGI. Solid background in AWS/GCP/Azure, Kubecost, and GPU cost optimisation techniques. Strong skills ...

Databricks. You'll work as a peer of the platform engineering teams. Rigour in running AI in production: experiment tracking and model registry (MLflow), evaluation frameworks and regression testing before release, monitoring and data-drift management, LLM observability and model governance. A track record of owning technical decisions across model ...

workloads in production (AWS or similar). Evaluation and observability for AI — hands‐on with tools like LangFuse, LangSmith, Braintrust, or MLflow — plus solid automated testing and CI/CD. Proven technical leadership — mentoring engineers, driving technical vision, and delivering complex, cross‐team projects. English — advanced proficiency, written and spoken. ...

experience with Generative AI and LLM deployment patterns. A proven history of reducing cloud spend on large-scale AI clusters. Experience with tools like MLflow, Kubeflow, LangSmith, or Phoenix. Expertise in AWS/GCP/Azure cost tools, Kubecost, or Cloudability. Extensive background of Kubernetes (K8s), Docker, and service meshes. ...

Docker, Helm, KubeFlow, and service meshes (e.g., Istio).Hands-on experience with Terraform, Ansible, GitHub Actions, ArgoCD, or Jenkins. Experience with vLLM, Ray, MLflow, LangChain/LangSmith, DeepSpeed, or Hugging Face TGI.Solid background in AWS/GCP/Azure, Kubecost, and GPU cost optimisation techniques. Strong skills in Python, Bash ...

enhance your day-to-day work. Technologies and Tools Python Machine learning frameworks (e.g. PyTorch, TensorFlow, scikit-learn) ML/MLOps tooling (e.g. SageMaker, MLflow, TFServing) Spark and Databricks AWS services (e.g. IAM, S3, Redis, ECS) CI/CD tooling and best practices Streaming and batch data systems (e.g. Kafka ...

evaluation, or human-in-the-loop annotation workflows. Experience with modern AI tools and platforms such as Databricks, PyTorch, Hugging Face, LangChain, LangGraph, Haystack, MLflow, or similar. Preferred qualificationsExperience in life sciences, pharmaceuticals, chemistry, biomedical research, clinical data. Familiarity with ontologies, taxonomies, controlled vocabularies, and metadata standards. Experience with ...

/ML lifecycle ownership—training pipelines, model deployment, versioning, monitoring, drift detection, observability (e.g., Weights & Biases, Arize), and lifecycle management using platforms such as MLflow, Vertex AI, or SageMaker. Cloud AI Platforms: Demonstrated deployment of AI workloads on AWS, GCP, and/or Azure including managed ML services, scalable inference ...

/ML lifecycle ownership: training pipelines, model deployment, versioning, monitoring, drift detection, observability (e.g., Weights & Biases, Arize), and lifecycle management using platforms such as MLflow, Vertex AI, or SageMaker* Cloud AI Platforms: Demonstrated deployment of AI workloads on AWS, GCP, and/or Azure including managed ML services, scalable inference ...

/ML lifecycle ownership: training pipelines, model deployment, versioning, monitoring, drift detection, observability (e.g., Weights & Biases, Arize), and lifecycle management using platforms such as MLflow, Vertex AI, or SageMakerCloud AI Platforms: Demonstrated deployment of AI workloads on AWS, GCP, and/or Azure including managed ML services, scalable inference infrastructure ...

structures, algorithms, machine learning, data mining, information retrieval, and statistics Knowledge of Kubernetes (AWS EKS) Experience training models in Databricks and SageMaker Experience with MLFlow Practical RAG experience with retrieval quality, embeddings, and vector stores Expert knowledge of at least one of AWS, Azure, or Kubernetes Knowledge of data management ...

Glue, Athena, Iceberg, Vertex AI, BigQuery, GCS, Cloud Run, or Pub/Sub. Experience with AI/ML observability and evaluation tools such as MLflow, LangSmith, LLM-as-a-Judge, guardrails, or production monitoring. Exposure to fine-tuning or continuous learning techniques, such as PEFT/LoRA. #ICBCareers #ICBEngineering #J ...

OpenCV. Production experience on AWS, specifically Amazon SageMaker: training and processing jobs, pipelines, model registry, endpoints. Practical MLOps: experiment tracking and model versioning with MLflow, hyperparameter optimisation, and reproducible, configuration‐driven training runs. Containerisation and infrastructure as code: Docker and CUDA‐based GPU images, plus enough Terraform to ship your ...

OpenAI, AI Foundry or AI Search, with Docker and Kubernetes Understanding of schema validation frameworks (e.g., JSON Schema, Pydantic) and MLOps tools such as MLflow or Airflow Strong communication ability to explain trade-offs around cost, latency and accuracy to technical and non-technical audiences Nice to have Experience using ...

Comfortable working with technical and non-technical stakeholders to deliver high-quality solutions. Even better if you have Databricks certifications. Experience with Unity Catalog, MLflow or Databricks Asset Bundles. Familiarity with dbt or similar data transformation frameworks. Exposure to Kafka, Event Hubs or other streaming technologies. Experience working with retail ...

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/ ...

OpenCV. Production experience on AWS, specifically Amazon SageMaker: training and processing jobs, pipelines, model registry, endpoints. Practical MLOps: experiment tracking and model versioning with MLflow, hyperparameter optimisation, and reproducible, configuration‐driven training runs. Containerisation and infrastructure as code: Docker and CUDA‐based GPU images, plus enough Terraform to ship your ...

/ML, or related field. Preferred Qualifications Certifications such as: CISSP, CISM, CCSPCertified AI Security (e.g., CAISP or similar)Experience with: MLOps platforms (e.g., MLflow, Kubeflow)AI red teaming and adversarial testingKnowledge of secure coding and DevSecOps practices. Familiarity with Responsible AI principles and ethical AI frameworks. Key Skills ...

OpenCV. Production experience on AWS, specifically Amazon SageMaker: training and processing jobs, pipelines, model registry, endpoints. Practical MLOps: experiment tracking and model versioning with MLflow, hyperparameter optimisation, and reproducible, configuration-driven training runs. Containerisation and infrastructure as code: Docker and CUDA-based GPU images, plus enough Terraform to ship your ...

scikit-learn, NumPy, LightGBM, Pandas, LangChain/LangGraph, TensorFlow, etc.) PySpark AWS cloud infrastructure: EMR, ECS, Athena, etc MLOps/DevOps: Terraform, Docker, Airflow, MLFlow Monitoring and evaluation platforms including New Relic and Braintrust More information Enjoy fantastic perks like private healthcare & dental insurance, a generous work from abroad policy ...

with data engineers on performance optimization, cost control, and platform capabilities MLOps & AI Platform (20%) Build ML model deployment pipelines using Azure ML, Databricks MLflow, or both Implement model versioning, experiment tracking, and model registry patterns Establish inference endpoints (batch and real‐time) with proper monitoring and governance Create reusable ...

least one of AWS, Azure or GCP. Strong troubleshooting and problem-solving skills. A Computer Science or related technical background. Experience with Unity Catalog, MLflow, CI/CD, Terraform or Databricks certification would be a bonus. About 7Dxperts 7Dxperts helps organisations solve complex challenges using Data, Spatial and Machine Learning ...

modelling, ETL and ELT processes, data quality, security and governance Ability to collaborate effectively with technical and non-technical stakeholders Experience with Unity Catalog, MLflow or Databricks Asset Bundles would be advantageous Knowledge of dbt, Kafka, Event Hubs or other data transformation and streaming technologies would be beneficial Desirable Experience ...