25 of 25 MLflow Jobs in the UK

/C++, Java, Go Machine Learning & AI stacks, including: TensorFlow, PyTorch, Scikit-learn, Transformers, LLMs. Customization: fine-tuning, RAG, other related methods. MLOps & DevOps: MLflow, TFX, Kubeflow, Docker, Kubernetes, CI/CD terminology and pipelines in GIT, Jira Cloud & Infrastructure: AWS BedRock, SageMaker AI, Azure Machine Learning, GCP Vertex ...

Purview) Drive scalable lakehouse architectures (Delta Lake, Iceberg, Hudi) Cloud, Infrastructure & MLOps Champion multi-cloud engineering across Azure, AWS, and GCP Lead MLOps strategy (MLflow, Kubeflow, SageMaker, Vertex AI) and CI/CD pipelines Ensure scalable deployments using Kubernetes, Docker, and Infrastructure-as-Code Enterprise Integration (.NET Focus) Integrate ...

problem-solving skills and attention to detail Desirable Skills Experience with big data technologies (e.g., Spark, Hadoop) Knowledge of MLOps practices and tools (e.g., MLflow, Kubeflow) Experience working with NLP, computer vision, or recommendation systems Understanding of data governance and security best practices Qualifications Bachelor's or Master's degree ...

analytics workloads Cloud, Infrastructure & MLOps Champion multi-cloud engineering across Azure, AWS, and GCP within an enterprise-grade environment Lead MLOps strategy (MLflow, Kubeflow, SageMaker, Vertex AI) and industrialised CI/CD pipelines Ensure scalable, secure deployments using Kubernetes, Docker, and Infrastructure-as-Code Enterprise Integration (.NET Focus) Integrate ...

LangChain and LangSmith/LangFuse Supervised fine-tuning or lightweight tuning (LoRA, PEFT) RAG evaluation techniques and model feedback loops MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes) · Familiarity with: AgentOps concepts (agent evaluation, monitoring) Basic telemetry/observability workflows (OpenTelemetry) Understanding of how domain-specific datasets influence AI behavior. ...

Environment Python, Java Cloud platforms AWS Containerisation and infrastructure-as-code tools Relational and non-relational databases Amazon Bedrock, Sagemaker, Vertex AI Datadog, Databricks, MLFlow, Grafana, OTel Claude, Gemini, ChatGPT, open-weight LLM models Terraform, Docker, K8s RMDBs, Graph DBs, Vector DBs Claude Code Github (and Github actions) Benefits Competitive ...

solutions in production cloud environments. Python: Strong capability in developing production-quality AI/ML code. LLMOps & AI Model Management: Familiarity with tools like MLFlow, LangChain, Hugging Face, Kubeflow, or similar platforms. Data Processing: Working knowledge of Databricks/Spark or comparable large-scale data processing tools. SQL: Solid capabilities ...

delivering business value Proficiency in Python and ML/DL frameworks (e.g., scikit-learn, PyTorch, TensorFlow) Experience with AI/ML tools (e.g., Jupyter, MLflow, Vertex AI, Azure ML, Amazon SageMaker Experience of creating delivery client-facing proof of concepts Strong knowledge of cloud platforms (Azure, AWS, GCP) and MLOps ...

LLMs, Generative AI, Agentic workflows. Engineering: PEFT, Vector Databases (Pinecone/Milvus/Weaviate), Prompt Engineering. Ops: Docker, Kubernetes, CI/CD, Experiment Tracking (MLflow/W&B). Data: ETL/ELT, Feature Stores, Performance Tuning. Who You Are A Technical Lead: You can bridge the gap between Data ...

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). ...

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 ...

GraphQL APIs Cloud & Infra: AWS (ECS, S3, Lambda), Docker, Cloudformation, Pulumi, CI/CD with GitHub Actions ML/AI: PyTorch, TensorFlow, scikit‐learn, MLflow for experiment tracking, Zenml for ML pipelines Data: PostgreSQL, DynamoDB, data pipelines with Zenml (We’re open to evolving the stack and expect ...

Strong Python skills and experience with ML libraries and frameworks (e.g. TensorFlow, PyTorch) Knowledge of statistics and probability Experience with ML lifecycle tools (e.g. MLflow, Kubeflow, Argo) Understanding of Ethical and Responsible AI principles Security Requirements You must hold active UK Developed Vetting (DV) clearance. ...

Hugging Face ecosystem Experience with audio or speech models and frameworks. Experience building and maintaining end-to-end ML pipelines and MLOps tooling (e.g. MLflow, Weights & Biases, DVC, or similar). Strong Python skills; experience with Docker, CI/CD, and cloud platforms (Azure preferred) Practical experience designing agentic ...

design. Desirable (AI & Data) Vector DBs: Milvus, Weaviate, Pinecone Data orchestration: Airflow, Prefect, Dagster Search: ElasticSearch/OpenSearch AI frameworks: LangChain, Hugging Face MLOps: MLflow, Kubeflow If you are looking for an opportunity to work on mission-critical systems at the forefront of UK National Security? Apply ...

/FSDP, DeepSpeed, or similar) Docker containerisation and multi-stage builds Cloud infrastructure (GCP preferred) and Infrastructure-as-Code (Terraform preferred) Experiment tracking (MLflow preferred) and CI/CD (GitHub Actions preferred) Multi-modal data pipelines Useful: ML infrastructure for robotics, autonomous vehicles, or embodied AI Cloud GPU orchestration tools ...

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 ...

Production-grade ML pipelines Model governance & lifecycle management Feature engineering at scale Embedding ML into agent-based systems Core stack Python · scikit-learn · MLflow · SQL · Docker · Feature Stores Nice to have Explainable AI · Anomaly Detection · LLM/NLP integration · Real-time inference ...

versioning, monitoring, and CI/CD automation. Build container-oriented ML platforms (EKS-first) while evaluating alternative orchestration tools with similar capabilities (Kubeflow, SageMaker, MLflow, Airflow, etc.). Implement hybrid MLOps + LLMOps workflows, including prompt/version governance, evaluation frameworks, and monitoring for LLM-based systems. Serve … Gateway, CI/CD (CodeBuild/CodePipeline or equivalent). Hands-on experience with at least one major MLOps toolset and awareness of alternatives: MLflow, Kubeflow, SageMaker Pipelines, Airflow, BentoML, KServe, Seldon. Deep understanding of model lifecycle management (feature engineering->training → registry → deployment → monitoring). Experience implementing or supporting LLMOps ...

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 Developer (Machine Learning AWS) you will earn a competitive package ...

applications , including data-driven and intelligent systems Support model training, fine-tuning, and deployment where experience allows Work with tools and approaches such as: MLflow and model lifecycle tools Gradient boosted trees or custom model development AI application frameworks (e.g. LangChain, RAG-style architectures) Experience across both AI application development ...

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 ...

Senior ML/MLOps Engineer (MLflow) | Databricks | Azure) About Optima Partners We’re an advanced data & business consultancy helping major consumer brands transform through data-driven customer strategy, design, and engineering. Our clients include leading UK and global brands across financial services, retail, and more. Join a practitioner-led, fast … loves building real, production grade ML systems not just proof‐of‐concepts. If you enjoy working across the full ML lifecycle and have strong MLflow experience, this role is built for you. What You’ll Do Own end-to-end ML model lifecycles from training to deployment to monitoring Productionise ...

Enterprise Sales Director, Public Sector London, United Kingdom SLSQ227R272 Do you want to help solve the world's toughest problems with big data and AI? This is what we do every day at Databricks! Leading ...

GAQ127R85 Mission Reporting to the EMEA People Partner Director, the Staff People Partner is a strategic advisor and catalyst for organisational excellence, partnering closely with senior leaders across Databricks’ European footprint. This role operates at ...