1 to 25 of 134 MLflow Jobs in the UK

Python and experience with core data science and ML libraries (e.g., scikit-learn, pandas, PyTorch or TensorFlow). Practical experience with Databricks, including MLflow for experiment tracking and model management, and Spark-based data processing. Familiarity with Generative AI concepts and tooling, including working with LLMs, prompt engineering, RAG patterns ...

pipelines. Ability to analyse large datasets and communicate insights effectively. Experience with LLMs, generative AI, and prompt engineering. Knowledge of MLOps tools and frameworks (MLflow, Kubeflow, Airflow). Familiarity with SQL, NoSQL, and distributed data technologies. Experience deploying AI models in production environments. Publications, patents, or open-source contributions ...

pipelines. Ability to analyse large datasets and communicate insights effectively. Experience with LLMs, generative AI, and prompt engineering. Knowledge of MLOps tools and frameworks (MLflow, Kubeflow, Airflow). Familiarity with SQL, NoSQL, and distributed data technologies. Experience deploying AI models in production environments. Publications, patents, or open-source contributions ...

pipelines. Ability to analyse large datasets and communicate insights effectively. Experience with LLMs, generative AI, and prompt engineering. Knowledge of MLOps tools and frameworks (MLflow, Kubeflow, Airflow). Familiarity with SQL, NoSQL, and distributed data technologies. Experience deploying AI models in production environments. Publications, patents, or open-source contributions ...

pipelines. Ability to analyse large datasets and communicate insights effectively. Experience with LLMs, generative AI, and prompt engineering. Knowledge of MLOps tools and frameworks (MLflow, Kubeflow, Airflow). Familiarity with SQL, NoSQL, and distributed data technologies. Experience deploying AI models in production environments. Publications, patents, or open-source contributions ...

equivalent multi-node training frameworks. Inference & serving: NVIDIA Triton, vLLM, TensorRT-LLM, or equivalent high-throughput serving platforms. MLOps/LLMOps: Kubeflow, MLflow, and at least one hyperscaler ML platform (SageMaker, Azure ML, or Vertex AI). Generative AI: LLM fine-tuning (LoRA/QLoRA), RAG architecture design, vector databases ...

security certifications. Experience deploying ML models into production environments. Experience with Kubernetes, OpenShift, or cloud-native deployment architectures. Experience with MLOps tooling (e.g. MLflow, Kubeflow, model monitoring platforms). Experience applying DevSecOps practices within cloud or controlled environments. Exposure to large language models or generative AI systems. Experience with data ...

experience in Artificial Intelligence, Software Engineering, Data Science or a related discipline. Eligible to obtain UK Security Clearance (SC). DESIRABLE SKILLS: Experience with MLflow, Weights & Biases or similar experiment-tracking tools. Experience with Spark or large-scale data processing platforms. Knowledge of ONNX, TorchScript, FastAPI or gRPC. Experience deploying ...

functional teams. Desirableskills andexperience: Experience building platforms or applications that support Data Science, Machine Learning, or AI workloads. Experience with MLOps tooling such as MLflow, Kubeflow, Vertex AI, or similar technologies. Knowledge of workflow orchestration platforms such as Apache Airflow. Experience with data processing technologies such as Pandas, Apache Beam ...

Studio, OpenAI, AKS), GCP (Vertex AI, Cloud Run), AWS (Bedrock, SageMaker)* Experience building and automating AI/ML pipelines using tools such as MLflow, Kubeflow, Azure ML, Vertex Pipelines, Airflow or Google ADK* Hands-on experience with Generative and Agentic AI frameworks such as LangChain, LlamaIndex, CrewAI, Autogen, Google ...

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 Familiarity with LLMOps tooling such as LangSmith, LangChain ...

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 Familiarity with LLMOps tooling such as LangSmith, LangChain ...

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 Familiarity with LLMOps tooling such as LangSmith, LangChain ...

model optimization, quantization, or deployment to edge devices. Familiarity with MLOps tools and practices: CI/CD, monitoring, and orchestration frameworks (e.g., Kubeflow, Flyte, MLflow); proficiency with Docker and Kubernetes for AI workload containerization. Hands‐on experience designing RAG pipelines and/or multi‐agent systems.. Understanding of sizing ...

similar. Experience with MLOps practices such as model deployment, monitoring, versioning or model registries. Exposure to workflow orchestration or deployment tools such as Airflow, MLflow, Azure DevOps, GitHub Actions or similar. Experience in pricing, insurance, financial services or another regulated environment. Understanding of model governance, responsible AI or explainability. Interview ...

services such as AWS SageMaker or AWS Bedrock. Experience with event‐driven processing, vector databases, and machine learning lifecycle tools such as Kafka and MLflow, or comparable technologies. Experience establishing observability and diagnosing production issues using tools such as Datadog or OpenSearch. Sound judgement when balancing delivery speed, quality, reliability ...

machine learning, data mining, information retrieval, and statistics Knowledge of Kubernetes (AWS EKS) Experience with training models in Databricks and SageMaker Experience working with MLFlow Practical RAG experience - retrieval quality, embeddings, and vector stores; Graph RAG a strong plus Expert knowledge of at least one of: AWS, Azure, Kubernetes Knowledge ...

worked with MLOps in practice rather than in principle: model versioning and registries, experiment tracking, automated retraining, and monitoring for drift and model degradation (MLflow, SageMaker, Databricks ML, Vertex AI or comparable) Are comfortable with ML frameworks such as scikit-learn, PySpark MLlib, or PyTorch/TensorFlow, enough to productionise ...

worked with MLOps in practice rather than in principle: model versioning and registries, experiment tracking, automated retraining, and monitoring for drift and model degradation (MLflow, SageMaker, Databricks ML, Vertex AI or comparable) Are comfortable with ML frameworks such as scikit-learn, PySpark MLlib, or PyTorch/TensorFlow, enough to productionise ...

worked with MLOps in practice rather than in principle: model versioning and registries, experiment tracking, automated retraining, and monitoring for drift and model degradation (MLflow, SageMaker, Databricks ML, Vertex AI or comparable) Are comfortable with ML frameworks such as scikit-learn, PySpark MLlib, or PyTorch/TensorFlow, enough to productionise ...

worked with MLOps in practice rather than in principle: model versioning and registries, experiment tracking, automated retraining, and monitoring for drift and model degradation (MLflow, SageMaker, Databricks ML, Vertex AI or comparable) Are comfortable with ML frameworks such as scikit-learn, PySpark MLlib, or PyTorch/TensorFlow, enough to productionise ...

solving skills and attention to detail Experience with LLMs and generative AI (OpenAI, Hugging Face, LangChain) Knowledge of NLP or computer vision Experience with MLflow, Kubeflow or similar MLOps tools What We Offer ✓ Competitive salary based on experience ✓ Diverse AI projects across multiple industries ✓ Collaborative and research-driven team environment ...

with technical and business stakeholders. Desirable Experience with Unity Catalog or similar data governance frameworks. Experience with Terraform or Databricks Asset Bundles. Exposure to MLflow, MLOps or AI and Generative AI workloads. Experience with streaming technologies such as Kafka or Structured Streaming. Databricks certification. Previous consulting or client-facing delivery ...

capabilities and skills Proficiency in coding in recent versions of Java and/or Python programming languages Experience with MLOps tools and platforms (e.g., MLflow, Amazon SageMaker, Google VertexAI, Databricks, BentoML, KServe, Kubeflow) Experience with cloud technologies (AWS/Azure/GCP) and distributed systems, web technologies and event drive ...

software development and implementation of AI/ML systems using cutting-edge technologies such as Python, R, Docker, Kubernetes, and tools like Azure Databricks, MLflow, and Google Vertex AI. Highly Valued Requirements Advanced Education: Master's or Ph.D. in big data, artificial intelligence, or related fields. Consulting Experience: Prior work ...