1 to 25 of 40 MLflow Jobs in the South East

Data Manipulation (SQL, Pandas, Pyspark) Azure AI (Azure AI Foundry, AI Search, Document Intelligence, AI Services) Data Science & Machine Learning (Databricks, Python, SKLearn, XGBoost, MLFlow, EDA) Familiarity with LLMs (OpenAI, Prompt Engineering, LangChain) Relevant Azure Data & Computation services (ADLS, ADF, Databricks, SQL Databases) Supporting: Azure ML Services React/ ...

experience developing, evaluating and orchestrating agentic workflows MLOps and Distributed Systems: Hands-on experience with distributed systems and MLOps tooling such as Kubernetes, Docker, MLflow, Airflow, Terraform, and CI/CD. Preferred Skills Data Streaming and Orchestration: Familiarity with tools such as Kafka, Flink, Spark, dbt, and Airflow. Multi-Modal ...

experience developing, evaluating and orchestrating agentic workflows MLOps and Distributed Systems: Hands-on experience with distributed systems and MLOps tooling such as Kubernetes, Docker, MLflow, Airflow, Terraform, and CI/CD. Preferred Skills Data Streaming and Orchestration: Familiarity with tools such as Kafka, Flink, Spark, dbt, and Airflow. Multi-Modal ...

experience developing, evaluating and orchestrating agentic workflows MLOps and Distributed Systems: Hands-on experience with distributed systems and MLOps tooling such as Kubernetes, Docker, MLflow, Airflow, Terraform, and CI/CD. Preferred Skills Data Streaming and Orchestration: Familiarity with tools such as Kafka, Flink, Spark, dbt, and Airflow. Multi-Modal ...

experience developing, evaluating and orchestrating agentic workflows MLOps and Distributed Systems: Hands-on experience with distributed systems and MLOps tooling such as Kubernetes, Docker, MLflow, Airflow, Terraform, and CI/CD. Preferred Skills Data Streaming and Orchestration: Familiarity with tools such as Kafka, Flink, Spark, dbt, and Airflow. Multi-Modal ...

experience developing, evaluating and orchestrating agentic workflows MLOps and Distributed Systems: Hands-on experience with distributed systems and MLOps tooling such as Kubernetes, Docker, MLflow, Airflow, Terraform, and CI/CD. Preferred Skills Data Streaming and Orchestration: Familiarity with tools such as Kafka, Flink, Spark, dbt, and Airflow. Multi-Modal ...

experience developing, evaluating and orchestrating agentic workflows MLOps and Distributed Systems: Hands-on experience with distributed systems and MLOps tooling such as Kubernetes, Docker, MLflow, Airflow, Terraform, and CI/CD. Preferred Skills Data Streaming and Orchestration: Familiarity with tools such as Kafka, Flink, Spark, dbt, and Airflow. Multi-Modal ...

experience developing, evaluating and orchestrating agentic workflows MLOps and Distributed Systems: Hands-on experience with distributed systems and MLOps tooling such as Kubernetes, Docker, MLflow, Airflow, Terraform, and CI/CD. Preferred Skills Data Streaming and Orchestration: Familiarity with tools such as Kafka, Flink, Spark, dbt, and Airflow. Multi-Modal ...

experience developing, evaluating and orchestrating agentic workflows MLOps and Distributed Systems: Hands-on experience with distributed systems and MLOps tooling such as Kubernetes, Docker, MLflow, Airflow, Terraform, and CI/CD. Preferred Skills Data Streaming and Orchestration: Familiarity with tools such as Kafka, Flink, Spark, dbt, and Airflow. Multi-Modal ...

experience developing, evaluating and orchestrating agentic workflows MLOps and Distributed Systems: Hands-on experience with distributed systems and MLOps tooling such as Kubernetes, Docker, MLflow, Airflow, Terraform, and CI/CD. Preferred Skills Data Streaming and Orchestration: Familiarity with tools such as Kafka, Flink, Spark, dbt, and Airflow. Multi-Modal ...

experience developing, evaluating and orchestrating agentic workflows MLOps and Distributed Systems: Hands-on experience with distributed systems and MLOps tooling such as Kubernetes, Docker, MLflow, Airflow, Terraform, and CI/CD. Preferred Skills Data Streaming and Orchestration: Familiarity with tools such as Kafka, Flink, Spark, dbt, and Airflow. Multi-Modal ...

Infrastructure as Code (Terraform), Docker - containerisation. An understanding of kubernetes. Understanding of LLM architectures, inference serving optimization techniques (quantisation, caching), and MLOps tooling (e.g., MLFlow, Kubeflow). Proven experience designing, implementing, and optimising complex RAG pipelines using vector databases (e.g., Pinecone, PGVector). Practical experience with agentic frameworks (e.g., LangChain ...

Langsmith/Langfuse, Gen AI/Agentic AI, Cloud platforms (Azure AI Foundry, AWS Sagemaker/Bedrock, GCP Vertex AI), MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes). Note: Applicants for employment in United Kingdom should possess work authorization which does not require sponsorship by the employer ...

Tools: Airflow, dbt, Databricks, Snowflake Developer Tooling & CI/CD: GitHub, Azure DevOps, Terraform (or other Infrastructure-as-Code tools) MLOps/LLMOps Frameworks: MLflow, AzureML, LangSmith ...

/CD, version control, and DevOps practices. Nice-to-Have Experience with streaming technologies (e.g., Spark Structured Streaming, Event Hub, Kafka). Knowledge of MLflow, Unity Catalog, or advanced Databricks features. Exposure to Terraform or other IaC tools. Experience working in Agile/Scrum environments. To apply for this role ...

users. Strong proficiency in containerisation (Docker, Kubernetes) and orchestration of multi-stage ML workflows. Hands-on experience with ML platforms and tools such as MLflow, Kubeflow, Vertex AI, SageMaker, or similar model management systems. Practical knowledge of infrastructure as code, CI/CD best practices, and cloud platforms ...

Computer Science, Data Science, Bioinformatics, Engineering, or a related field, or equivalent experience. Proven experience designing and deploying MLOps pipelines (MLflow, Azure ML, Azure DevOps etc). Strong programming skills in Python and familiarity with common ML/AI libraries (scikit-learn, tensorflow, Keras etc.). Experience implementing machine learning ...

pipelines and cloud environments (we use Azure) Strong communication skills and a collaborative mindset Preferred Skills Experience with model versioning and experiment tracking (e.g. MLflow, Weights & Biases) Understanding of optimizing both CPU-bound and GPU-bound workloads Knowledge of monitoring and observability tools (e.g. Prometheus, Grafana, ELK stack) Background ...

deploying cutting-edge machine learning solutions across the company.If you enjoy end-to-end ownership (from experimentation to deployment), working with AWS, Docker, MLflow, TensorFlow/PyTorch, and contributing to innovative projects with a flexible, results-focused culture, this could be an exciting match. Skills: Ability to write and produce ...

Strong design and development skills using Python. Python's libraries for machine learning: PySpark, Pytorch, scikit-learn and pandas. Technical experience using Databricks and MLFlow (Other Platforms can be considered). Good understanding of software code review standards - CI/CD. Stochastic Simulation modelling experience. If you are interested ...

industry experience. Essential Skills Excellent knowledge and experience of managing an on-premise Kubernetes cluster. Excellent knowledge of Kubeflow and similar systems, e.g. MLflow Good programming ability in Python with familiarity with Linux systems including scripting and system configuration. Experience using AWS, e.g, Cognito, S3, EC2, Lamdas, etc. Experience with ...

library skills Hands-on experience with GenAI APIs and production deployments Knowledge of the full ML lifecycle and MLOps tools such as MLflow or SageMaker Strong communication skills and experience working with senior stakeholders A grounding in statistics and an agile, problem solving mindset Some Scala exposure is a bonus ...

Machine Learning Engineer Machine Learning Engineer – AI for Advanced Materials – Oxford (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We're looking for a Machine Learning Engineer to join … Machine Learning Engineers with experience in some or all of the following (full training provided to fill any gaps): Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, Pandas, NumPy, SciPy, CI/CD, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform, Azure, AWS, GCP, Git, and Agile methodologies. Join ...

Machine Learning Engineer Machine Learning Engineer - AI for Advanced Materials - Oxford (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We're looking for a Machine Learning Engineer to join … Machine Learning Engineers with experience in some or all of the following (full training provided to fill any gaps): Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, Pandas, NumPy, SciPy, CI/CD, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform, Azure, AWS, GCP, Git, and Agile methodologies. Join ...

LangChain, LangGraph, or custom). Create and maintain data pipelines (Airflow, dbt, Step Functions). Implement monitoring, observability, and automated retraining (CloudWatch, Prometheus, Grafana, MLflow). Embed strong security, compliance, and guardrail practices across all ML workflows. Mentor junior engineers and promote engineering best practices. Key Requirements Essential 3+ years … SageMaker, EKS/Fargate, Lambda, Step Functions, S3). Proficient with Docker, Kubernetes , and IaC (Terraform or AWS CDK). Experience with MLflow , CI/CD tools, and automated testing. Hands-on with LLM deployment and multi-agent systems . Proven experience building data pipelines and production ML workflows. Strong ...