51 to 75 of 153 MLflow Jobs in England

following AI/ML frameworks: Huggingface, Torch, Tensforflow, Scikit-Learn, and Spacy* Experience in of any of the following additional platforms related to MLOps: MLFlow, dbt, Docker, Kubernetes.* Experience with working cloud environments such as AWSTechnical Concept Requirements* Experience in any of the following AI/ML topics within ...

/ML lifecycle ownership—training pipelines, model deployment, versioning, monitoring, drift detection, observability (e.g., Weights & Biases, Arize), and lifecycle management using platforms such as MLflow, Vertex AI, or SageMaker. Cloud AI Platforms: Demonstrated deployment of AI workloads on AWS, GCP, and/or Azure including managed ML services, scalable inference ...

/ML lifecycle ownership: training pipelines, model deployment, versioning, monitoring, drift detection, observability (e.g., Weights & Biases, Arize), and lifecycle management using platforms such as MLflow, Vertex AI, or SageMaker* Cloud AI Platforms: Demonstrated deployment of AI workloads on AWS, GCP, and/or Azure including managed ML services, scalable inference ...

/ML lifecycle ownership: training pipelines, model deployment, versioning, monitoring, drift detection, observability (e.g., Weights & Biases, Arize), and lifecycle management using platforms such as MLflow, Vertex AI, or SageMakerCloud AI Platforms: Demonstrated deployment of AI workloads on AWS, GCP, and/or Azure including managed ML services, scalable inference infrastructure ...

experience. Highly Desirable Familiarity with OneTick, PostgreSQL, ClickHouse, Snowflake, Databricks, kdb+ or similar. Order book reconstruction Tick-to-bar aggregation Airflow, Dagster, Prefect or MLflow Experience supporting quantitative research or trading systems Multi-asset market data (Equities, Futures, FX, Options, ETFs, CFDs) What We're Looking For The successful candidate ...

modern machine learning and data science frameworks. Hands-on experience with large language models, generative AI, prompt engineering, and RAG architectures. Experience with Databricks, MLflow, Spark, and cloud-based AI platforms (Azure preferred). Strong understanding of MLOps, software engineering best practices, and production deployment pipelines. Experience leading technical teams ...

problem statements and propose solutions considering effort, impact, and scalability trade-offs; Nice to have: Apache Spark, Iceberg, Kafka, dbt, Scikit-Learn, XGBoost, PyTorch, MLFlow, GraphFrames, Ray, AWS S3, EMR, SageMaker, Lakeformation, Terraform, Docker, GitHub CI/CD, Knowledge Graphs, RAG, graph ML, probabilistic programming, A/B testing. Условия ...

offs.Real-time & distributed ML: A strong grasp of production inference patterns, plus Spark and distributed data processing.Reproducibility & tooling: Reproducible environments (UV/Docker) and MLflow or equivalent, on AWS with Spark, Databricks and Snowflake.Engineering mindset: A focus on reliability, maintainability and continuous improvement.SummaryLocation: Holborn - LondonType: Full time ...

productionise models.Contribute to technical planning, architecture decisions and engineering best practices.Essential experienceStrong Python development skills.Experience with Machine Learning experiment tracking and model registries using MLflow, Weights & Biases, Neptune, ClearML or a similar platform.Experience with distributed training frameworks such as Ray, DeepSpeed, Horovod or PyTorch FSDP.Hands-on experience optimising models ...

observability (Ganglia, Prometheus, or Datadog).• Understanding of serverless Databricks clusters.• Familiarity with Terraform and infrastructure as code for Databricks resource management.• Exposure to MLflow and model-serving pipelines for end-to-end performance optimization.• Experience with Unity Catalog and fine-grained governance controls.Qualifications• Bachelor’s or Master’s degree ...

alongside DevOps technologies and practices such as Docker, Terraform, CI/CD pipelines and infrastructure-as-code.Familiarity with MLOps tools and practices such as MLflow, Airflow, model monitoring, API monitoring, data validation, data drift detection, autoscaling and access management.Strong Python experience, with helpful knowledge of Spark or PySpark for working ...

DevOps technologies and practices such as Docker, Terraform, CI/CD pipelines and infrastructure‐as‐code. Familiarity with MLOps tools and practices such as MLflow, Airflow, model monitoring, API monitoring, data validation, data drift detection, autoscaling and access management. Strong Python experience, with helpful knowledge of Spark or PySpark ...

Experience with Spark, agile delivery methods and CI/CD practices Familiarity with DevOps and MLOps tools and practices, such as Docker, Terraform and MLFlow Confidence influencing and communicating with stakeholders across technical and non-technical teams Ideally, exposure to cloud infrastructure, NLP or large language models (such as fine ...

functional teams to align data architecture with financial regulations (e.g., GDPR, Basel III, MiFID II). Drive adoption of Delta Lake , Apache Spark , and MLflow for advanced analytics and machine learning use cases. Provide technical leadership and mentoring to data engineers and analysts across financial domains such as risk, trading ...

insurance, mobile data, or behaviour modelling.Experience with cloud platforms (AWS), containerisation (Docker, Kubernetes), or data orchestration frameworks.Familiarity with our ML and tooling stack: MLflow for experiment tracking, DVC for data versioning, Streamlit for internal apps and demos.BenefitsWhat it’s like to work at ZegoAt Zego, we operate like a high ...

mobile data, or behaviour modelling. Experience with cloud platforms (AWS), containerisation (Docker, Kubernetes), or data orchestration frameworks. Familiarity with our ML and tooling stack: MLflow for experiment tracking, DVC for data versioning, Streamlit for internal apps and demos. BenefitsWhat it's like to work at ZegoAt Zego, we operate like ...

Distributed Training infrastructure (Multi-node GPU training, Kubernetes, vLLM).Familiarity with Deep Learning frameworks (PyTorch).Experience with MLOps tools and experiment tracking (e.g., ClearML, MLFlow, Weights & Biases).Research Fluency: Ability to read technical research papers and translate them into engineering requirements. You don't need to write the paper ...

Programming skills in Python, SQL, or ScalaProficiency in data modelling, ETL/ELT processes, and data architectureExperience in MS Copilot, AI Foundry , Databricks (MosiacAI, MLflow, Agentbricks, Genie)Strong analytical background with problem-solving skillsPerformance tuning concepts like watermarking, late data handling, parallelism & checkpointingHands-on expertise in ADF, and Qlik Replicate ...

constraints. Nice to Have Experience with GPU cluster management and ML training workloads (NVIDIA, CUDA, distributed training). Familiarity with MLOps tooling: Experiment tracking (MLflow, Weights & Biases). Workflow orchestration (Airflow, Prefect, Argo). Data versioning (DVC). Background in scientific computing or HPC environments. Prior experience at a deep ...

Demonstrate familiarity with Markets Operations processes such as trade lifecycle, post-trade operations, reconciliations, controls, or exception management Use AWS and tools such as MLflow Develop front-end capabilities with React or modern front-end development Apply graph database modeling concepts Why Join Us? Your contributions will help redefine what ...

Demonstrate familiarity with Markets Operations processes such as trade lifecycle, post-trade operations, reconciliations, controls, or exception management Use AWS and tools such as MLflow Develop front-end capabilities with React or modern front-end development Apply graph database modeling concepts Why Join Us? Your contributions will help redefine what ...

ability to write clear documentation and collaborate across engineering teams. Ecosystem Knowledge : Hands‐on experience supporting software delivery and MLOps tooling (e.g., Kubernetes, Kubeflow, MLflow, Triton, Docker, or SageMaker/Azure ML). Equal Opportunity Statement We are committed to fostering and promoting an inclusive professional environment ...

testing and experimentation frameworks for AI features Contributions to open‐source ML projects or research publications 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 ...

batch data extraction processes, particularly those built in Python and orchestrated using Airflow Understanding of machine learning tooling and lifecycle management, ideally including DVC, MLflow, Evidently AI, or equivalent platforms for experiment tracking, versioning, monitoring, and evaluation Ability to work effectively across a data ecosystem that uses a range ...

ability to write clear documentation and collaborate across engineering teams. Ecosystem Knowledge : Hands-on experience supporting software delivery and MLOps tooling (e.g., Kubernetes, Kubeflow, MLflow, Triton, Docker, or SageMaker/Azure ML) Equal Opportunity Statement We are committed to fostering and promoting an inclusive professional environment ...