76 to 100 of 137 MLflow Jobs in London

Excellent understanding of statistics, machine learning methodologies, and model evaluation. Experience delivering AI solutions from proof-of-concept through to production. Exposure to Databricks, MLflow, Spark, or similar cloud-based data platforms. Ability to influence senior stakeholders and lead technical strategy Desirable Experience Experience building multi-agent AI systems ...

similar enterprise planning platforms Experience with A/B testing and experimentation frameworks for AI features Experience with model observability tools (LangSmith, W&B, MLflow) Our Commitment to Diversity, Equity, Inclusionand Belonging (DEIB) We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB ...

regulated workflows requiring auditable LLM output Experience with OpenFGA or OPA/Rego, service mesh technologies, and micro-VM isolation Experience with Databricks, MLflow, and model serving on Kubernetes, including GPU capacity planning and small language model inference Experience with knowledge graphs, GraphRAG, or organizational memory for agents Experience with ...

experience with LLMs and agentic systems [Preferred] Hands-on experience with technologies in the modern AI/LLM ecosystem, such as Databricks, Langchain, or MLFlow [Preferred] Advanced understanding of the probabilistic systems underpinning modern LLMs [Preferred] Experience building AI products in highly accuracy-sensitive domains such as finance ...

exposure to Spark or similar data processing tools You may also have some familiarity with DevOps or MLOps tools such as Docker, Terraform or MLflow Ideally, you will have an interest in agile ways of working and CI/CD practices, though this is not essential More information: Enjoy fantastic ...

e.g., Git) and collaborative development Experience in using computing environments Strong problem-solving skills and willingness to learn Desirable: Familiarity with MLOps tools (e.g. MLflow, Weights & Biases) Exposure to natural language processing (LLMs, agents), computer vision, or reinforcement learning We actively recruit citizens of all backgrounds, but the nature ...

Gemini, Claude and OpenAI APIs. Hands-on experience with AI tools/frameworks (e.g., Braintrust, AutoEval) and/or MLOps tools (e.g., Airflow, MLflow, Vertex AI, or similar). Solid understanding of data engineering practices, including ETL, batch/streaming pipelines, and data quality monitoring. Familiarity with cloud infrastructure ...

experience with LLMs and agentic systems[Preferred] Hands-on experience with technologies in the modern AI/LLM ecosystem, such as Databricks, Langchain, or MLFlow[Preferred] Advanced understanding of the probabilistic systems underpinning modern LLMs[Preferred] Experience building AI products in highly accuracy-sensitive domains such as finance ...

Autoloader) Programming skills inPython,SQL, orScala Proficiency indata modelling, ETL/ELT processes, and data architecture Experience in MS Copilot, AI Foundry , Databricks (MosiacAI, MLflow, Agentbricks, Genie) Strong analytical background with problem-solving skills Performance tuning concepts like watermarking, late data handling, parallelism & checkpointing Hands-on expertise inADF, and Qlik ...

with a clear focus on engineering and productionising machine learning modelsStrong hands-on development skills across Python, PySpark and SQLCommercial experience working with Databricks, MLflow and Delta LakeProven experience building and operating distributed data and machine learning pipelinesExperience taking Data Science models from notebooks or development environments into productionStrong understanding ...

audiences Preferred qualifications, capabilities, and skills Experience with agent frameworks and protocols (MCP, A2A, Google ADK, LangGraph) and agent evaluation practices Experience with Databricks, MLflow, and model serving on Kubernetes in AWS Experience delivering AI systems through model risk management or equivalent regulatory review Experience running a team within ...

English. Preferred Qualifications, Capabilities & Skills Product management experience for AI/ML, MLOps, or data platforms. Familiarity with MLOps concepts and frameworks, such as MLflow, Amazon SageMaker, and feature stores. Familiarity with AI concepts, such as Retrieval‐Augmented Generation (RAG), agentic system architectures, evaluation of LLMs and agents, and Model ...

learning, on-prem, or air-gapped deployment experience. Experience building self-serve ML platforms or tools for non-expert users. Experience with lakeFS, DVC, MLflow, Weights & Biases, Kubernetes, Kubeflow, Flyte, Dagster, Airflow, or Argo. LLM application, context engineering, structured output, or LLM evaluation experience. Exposure to radar, AIS, EO/ ...

lifecycle management Developer experience: APIs, SDKs, CLIs, notebooks Infrastructure: storage, networking, IAM, observability, infrastructure-as-code Familiarity with tools such as PyTorch, Ray, Slurm, MLflow, Langchain, Hugging Face, vLLM, Triton, or similar. Able to balance performance, cost, usability, flexibility, and reliability. Strong prioritisation, communication, and stakeholder management skills. Comfortable taking ...

with MongoDB or other NoSQL databases Experience with unsupervised methods such as clustering or hidden Markov models Experience with ML lifecycle tooling such as MLflow Experience with anomaly detection A background around boats, cars, bikes or planes We're less interested in ticking off niche experience like maritime or MongoDB ...

equivalent — and familiarity with what good looks like across different GPU generations and topologies. Exposure to MLOps tooling and AI platform layers: experiment tracking (MLflow, W&B), model serving frameworks (Triton, vLLM), and pipeline orchestration (Kubeflow, Airflow). Familiarity with InfiniBand and high-performance networking as it relates to distributed ...

binary classification problems Event streaming data engineering tools such as Flink or Spark Experience with MLOps and tools such as Airflow, BentoML and MLFlow Use of Docker CI/CD and SDLC (e.g. JIRA, Git, Jenkins, Octopus) Job type Permanent Skills DataScientist Why Zempler Bank We’re on a journey ...

product engineering—from architectural design and prototyping to CI/CD-enabled deployment—using modern platforms and tools such as Azure ML, Databricks, MLflow, LangChain and LangGraph. Champion automation, testing, and observability across pipelines.· Operational Excellence: Define reusable development patterns, enforce coding standards, and promote MLOps best practices that support … e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers).· Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks, MLflow, LangChain, LangGraph.· Proven experience with modern engineering practices Git, version control, unit testing and containerisation.· Familiarity with agile work methodologies and tools like Jira ...

teams. You Need Expert Python and SQL, with experience building production ML systems and data pipelines (PyTorch, XGBoost, Spark/PySpark, Apache Iceberg, Ray, MLflow, SageMaker, Airflow, or equivalent). Deep experimentation and statistical inference skills, and a strong grasp of optimisation under uncertainty (bandits, causal inference, off-policy evaluation ...

Terraform Monitoring and performance tuning of cloud-based applications and services Nice to haves: (MLOps): Model Deployment & Serving – Deploy and manage ML models using MLflow, Azure ML, SageMaker, or similar, ensuring scalability and performance. Monitoring & Retraining – Set up model drift detection, performance monitoring, and automated retraining ML Pipelines & CI/ ...

multiple layers Preferred Qualifications, Capabilities, and Skills: Experience with agent frameworks and protocols (Google ADK, LangGraph, MCP, A2A, AG-UI) Experience with Databricks, MLflow, Spark, and Delta Lake or Apache Iceberg Experience serving models on Kubernetes, including GPU workloads and fine-tuned small language models Experience with optimization or pricing ...

engineering fundamentals - you build reliable, well-tested, maintainable systems. Python, Kotlin/Java, SQL. Experience with ML orchestration (Airflow, Kubeflow, or equivalent), model registries (MLflow or similar), and container-based deployment End-to-end understanding of the ML lifecycle - data ingestion through training, packaging, serving, and monitoring - and knowledge ...

Managed Services on cloud and on prem AI/ML & MLOps - Open source AI/ML solutions, AIOps automation, model lifecycle management, Kubeflow, MLFlow, KServe, and AI infrastructure on cloud and edge IoT - Ubuntu on embedded devices and/or edge servers, device management, and robotics Cloud - Ubuntu in public ...

Lead technical implementation of pilot models on the Global AI Platform. Develop reusable migration accelerators and standards. Key Experience Databricks Lakehouse Platform. Databricks ML, MLflow, Unity Catalog, Workflows, and Model Serving. CI/CD and MLOps automation. Python and production ML deployment patterns. ...

Lead technical implementation of pilot models on the Global AI Platform. Develop reusable migration accelerators and standards. Key Experience Databricks Lakehouse Platform. Databricks ML, MLflow, Unity Catalog, Workflows, and Model Serving. CI/CD and MLOps automation. Python and production ML deployment patterns. ...