1 to 25 of 31 MLflow Jobs in England

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/ ...

Computer Science, Machine Learning, or a related technical discipline Bonus Skills/Experience Understanding of MLOps, model serving, scaling and monitoring workflows (e.g., BentoML, MLflow, Vertex AI, AWS Sagemaker) Experience building streaming + batch data ingestion and transformation pipelines (Spark/Airflow/Beam) Mobile and front-end web application ...

experience delivering end-to-end ML and GenAI solutions (including RAG, LLMs, embeddings and vector databases). Strong knowledge of MLOps tooling and practices (MLflow, CI/CD, containerisation, monitoring). Experience leading, mentoring and developing technical teams. If you'd like to learn more, please contact Jacob Ferdinand ...

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 ...

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 ...

vector databases and embedding stores, including Pinecone, Weaviate, Milvus, FAISS, ChromaDB, and pgVector. Implement LLMOps/PromptOps practices using tools such as: Weights & Biases, MLflow, LangSmith, LangFuse, PromptLayer, Humanloop, Helicone, Arize Phoenix Benchmark, evaluate, and monitor LLM systems using RAGAS, DeepEval, custom eval suites, and human-in-the-loop review. ...

vector databases and embedding stores, including Pinecone, Weaviate, Milvus, FAISS, ChromaDB, and pgVector. Implement LLMOps/PromptOps practices using tools such as: Weights & Biases, MLflow, LangSmith, LangFuse, PromptLayer, Humanloop, Helicone, Arize Phoenix Benchmark, evaluate, and monitor LLM systems using RAGAS, DeepEval, custom eval suites, and human-in-the-loop review. ...

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 ...

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 ...

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 ...

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. ...

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. ...

such as Amazon SageMaker . Comfortable with software version control (Git) and collaborative workflows. Experience with experiment tracking/management tools (e.g., SageMaker Studio , MLflow, Weights & Biases). Machine Learning Expertise Proven ability to build, test, and validate hypotheses through well-designed ML experiments. Hands-on experience creating and deploying ...

infrastructure (networking, identity, storage, Kubernetes). Support data lakes and warehouses (e.g., Snowflake). Enable data/ML platforms like Databricks, Azure ML, Synapse, MLflow, Airflow. Drive automation with Terraform, Azure DevOps, CI/CD pipelines. Embed security and compliance standards (GDPR, ISO 27001). What we're looking ...

infrastructure (networking, identity, storage, Kubernetes). Support data lakes and warehouses (e.g., Snowflake). Enable data/ML platforms like Databricks, Azure ML, Synapse, MLflow, Airflow. Drive automation with Terraform, Azure DevOps, CI/CD pipelines . Embed security and compliance standards (GDPR, ISO 27001). What we’re looking ...

they grow. Your Skills and Experience To succeed, you will bring strong commercial experience in: Python and applied ML engineering. MLOps tooling such as MLflow and modern experiment tracking platforms. Deploying models into production, including monitoring, testing and automation. AWS, with practical experience using SageMaker. Cloud and DevOps foundations including ...

Engineering with exposure to ML lifecycle. Hands-on experience building or maintaining ML workflows or pipelines. Strong Python skills and experience with tools like MLflow, Scikit-learn, or PyTorch. Familiarity with cloud platforms (especially Azure, AWS). Good understanding of containerisation (Docker) and orchestration (e.g. Kubernetes). Exposure … infrastructure-as-code (Terraform). Collaborative team player with excellent communication skills. Technical Stack: Languages: Python (primary), SQL, Bash Cloud: Azure, AWS Tools: MLflow, Azure ML, Airflow, Docker, Fargate, FastAPI Data: Snowflake, Delta Lake, Redis, Azure Data Lake Infra & Ops: Terraform, GitHub Actions, Azure DevOps, Grafana, Azure Monitor Desirable skills ...

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 ...

Requirements 2+ years MLOps experience Strong Python, ML engineering and deployment foundations. Hands-on experience with AWS and SageMaker (essential). MLOps best practice: MLflow, CI/CD for ML, monitoring, reproducibility. Cloud and DevOps knowledge: AWS, Docker, IaC (CDK preferred). Experience deploying scalable pipelines and ML endpoints. Collaborative ...

engineering. Proven experience in building and operating machine learning models. Experience in multiple technologies and frameworks required such as Azure Databricks, Azure ML, MLFlow, GIT, Python and PySpark and microservices. Strong understanding of software development, DevOps, MLOps and Agentic Ops practices and microservices. Excellent communication and collaboration skills. About ...

youll be setting direction. The tech youll work with Core:Azure, Databricks, Python, SQL, dbt, MQTT Storage & Serving:Delta Lake, Postgres, TimescaleDB Modelling & ML:MLflow Visualisation:Grafana What makes you a great fit Youre someone who can zoom out to architecture and zoom in to code, comfortably. Proven experience building ...

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 ...

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. ...

Details • Salary : £80,000 – £150,000 • Working model : On-site 3+ days/week with retail and consumer clients UK-wide • Tech stack : Python, MLflow, Databricks, Docker, Azure, simulation frameworks • Visa : This role cannot sponsor If you’re interested, please apply below. ...