1 to 25 of 165 MLflow Jobs in the UK excluding London

Solid understanding of supervised/unsupervised learning, deep learning, and model evaluation techniques. Cloud & MLOps: Experience with AWS, GCP, or Azure; Docker/Kubernetes; MLflow or similar tools. Data Handling: Familiarity with big data frameworks (Spark, Hadoop) and data versioning tools (DVC). Soft Skills: Strong problem-solving, communication ...

Experience: Experience with generative AI and large language models, including LangChain, vector databases and retrieval‐augmented generation Knowledge of AutoML, hyperparameter optimisation and advanced MLflow features. Experience working with streaming or real‐time data platforms Familiarity with CI/CD, MLOps and deployment pipelines (Azure DevOps, GitHub Actions, Docker). ...

Experience: Experience with generative AI and large language models, including LangChain, vector databases and retrieval‐augmented generation Knowledge of AutoML, hyperparameter optimisation and advanced MLflow features. Experience working with streaming or real‐time data platforms Familiarity with CI/CD, MLOps and deployment pipelines (Azure DevOps, GitHub Actions, Docker). ...

Experience: Experience with generative AI and large language models, including LangChain, vector databases and retrieval‐augmented generation Knowledge of AutoML, hyperparameter optimisation and advanced MLflow features. Experience working with streaming or real‐time data platforms Familiarity with CI/CD, MLOps and deployment pipelines (Azure DevOps, GitHub Actions, Docker). ...

Experience: Experience with generative AI and large language models, including LangChain, vector databases and retrieval‐augmented generation Knowledge of AutoML, hyperparameter optimisation and advanced MLflow features. Experience working with streaming or real‐time data platforms Familiarity with CI/CD, MLOps and deployment pipelines (Azure DevOps, GitHub Actions, Docker). ...

learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines Experience working with distributed data processing using PySpark. Solid understanding of software engineering principles and version control (e.g., Git). Excellent ...

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 ...

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 ...

Python (pandas, NumPy, scikit-learn; PyTorch/TF a plus). Feature engineering, data quality validation, model training and optimisation. MLOps: experiment tracking (e.g., MLflow), model registry, CI/CD for ML. Serving and orchestration: AWS SageMaker, EKS, batch & real-time inference. Data pipelines: Spark/SQL, orchestration (Airflow), monitoring ...

deep learning techniques (e.g., TF-IDF, word embeddings, CNNs, RNNs). Familiarity with generative AI and prompt engineering. Experience with Azure Databricks, MLflow, Azure ML services, Docker, or Kubernetes. Exposure to Agile development environments and software engineering best practices. Experience working in large, complex organisations or regulated industries. Strong working ...

deep learning techniques (e.g. TF-IDF, word embeddings, CNNs, RNNs). Familiarity with Generative AI and prompt engineering. Experience with Azure Databricks, MLflow, Azure ML services, Docker, Kubernetes. Exposure to Agile development environments and software engineering best practices. Experience working in large or complex organisations or regulated industries. Strong working ...

algorithms. Consulting Experience: Proven track record of delivering solutions in a client-facing consulting environment. MLOps Expertise: Hands-on experience with tools such as MLflow, Kubeflow, TensorFlow Serving, or similar. Cloud Platforms: Proficiency in multi-cloud environments (AWS, Azure, GCP). DevOps & Automation: Strong knowledge of CI/CD pipelines ...

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). ...

practices, version control (Git), or CI/CD pipelines Understanding of deep learning, NLP, or computer vision Familiarity with deployment tools like Docker or MLflow What You’ll Gain Hands-on Experience : Work on real ML systems and contribute to production-grade solutions Mentorship & Training : Learn from senior ML engineers ...

lifecycle management Lead documentation, knowledge transfer, and mentoring to upskill internal teams Technical requirements Strong Python and ML frameworks (PyTorch, TensorFlow) MLOps tooling (MLflow, Kubeflow or similar) Docker, Kubernetes, CI/CD pipelines Cloud platforms (AWS, Azure or GCP); Terraform experience preferred Financial services experience highly desirable A hands ...

working with large datasets and data pipelines Desirable Experience Experience with Generative AI or large language models Exposure to tools such as Hugging Face, MLflow, Kubeflow, or similar Knowledge of NLP, computer vision, or recommendation systems Experience working in agile or product-led environments Whats on Offer Competitive salary ...

embeddings, vector search, and Generative AI architectures. Practical experience using Hugging Face, OpenAI, LangChain, Retrieval Augmented Generation, and diffusion models. Strong MLOps experience including MLflow, Kubeflow, Airflow, Docker, Kubernetes, and CI and CD tooling. Strong programming skills in Python. Bash, SQL, and JavaScript are desirable. Proven experience working with large ...

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 ...

models in production environments. Knowledge of distributed training, GPU/TPU optimization, and cloud platforms (AWS, GCP, Azure). Familiarity with MLOps tools like MLflow, Kubeflow, or Vertex AI for scalable ML pipelines. Excellent leadership, communication, and cross-functional collaboration skills. Bachelor's or Master's in Computer Science, Engineering ...

models in production environments. Knowledge of distributed training, GPU/TPU optimization, and cloud platforms (AWS, GCP, Azure). Familiarity with MLOps tools like MLflow, Kubeflow, or Vertex AI for scalable ML pipelines. Excellent leadership, communication, and cross-functional collaboration skills. Bachelor's or Master's in Computer Science, Engineering ...

models in production environments. Knowledge of distributed training, GPU/TPU optimization, and cloud platforms (AWS, GCP, Azure). Familiarity with MLOps tools like MLflow, Kubeflow, or Vertex AI for scalable ML pipelines. Excellent leadership, communication, and cross-functional collaboration skills. Bachelor's or Master's in Computer Science, Engineering ...

models in production environments. Knowledge of distributed training, GPU/TPU optimization, and cloud platforms (AWS, GCP, Azure). Familiarity with MLOps tools like MLflow, Kubeflow, or Vertex AI for scalable ML pipelines. Excellent leadership, communication, and cross-functional collaboration skills. Bachelor's or Master's in Computer Science, Engineering ...

models in production environments. Knowledge of distributed training, GPU/TPU optimization, and cloud platforms (AWS, GCP, Azure). Familiarity with MLOps tools like MLflow, Kubeflow, or Vertex AI for scalable ML pipelines. Excellent leadership, communication, and cross-functional collaboration skills. Bachelor's or Master's in Computer Science, Engineering ...

models in production environments. Knowledge of distributed training, GPU/TPU optimization, and cloud platforms (AWS, GCP, Azure). Familiarity with MLOps tools like MLflow, Kubeflow, or Vertex AI for scalable ML pipelines. Excellent leadership, communication, and cross-functional collaboration skills. Bachelor's or Master's in Computer Science, Engineering ...

models in production environments. Knowledge of distributed training, GPU/TPU optimization, and cloud platforms (AWS, GCP, Azure). Familiarity with MLOps tools like MLflow, Kubeflow, or Vertex AI for scalable ML pipelines. Excellent leadership, communication, and cross-functional collaboration skills. Bachelor's or Master's in Computer Science, Engineering ...