1 to 25 of 33 MLflow Jobs in London

Purview) Drive scalable lakehouse architectures (Delta Lake, Iceberg, Hudi) Cloud, Infrastructure & MLOps Champion multi-cloud engineering across Azure, AWS, and GCP Lead MLOps strategy (MLflow, Kubeflow, SageMaker, Vertex AI) and CI/CD pipelines Ensure scalable deployments using Kubernetes, Docker, and Infrastructure-as-Code Enterprise Integration (.NET Focus) Integrate ...

field Proven experience building and implementing LLM‐based solutions (GPT, Claude, Llama, Mistral, or similar) Hands‐on experience with at least one of: Databricks (MLflow, AutoML), Azure Machine Learning, or Snowflake (Snowpark ML, Cortex) Understanding of natural language processing, computer vision, and recommender systems Strong programming skills in Python ...

libraries (scikit-learn, numpy, LightlGBM, Pandas, LangChain/LangGraph, TensorFlow, etc..) PySpark AWS cloud infrastructure: EMR, ECS, Athena, etc. MLOps: Terraform, Docker, Airflow, MLFlow More information: Enjoy fantastic perks like private healthcare & dental insurance, a generous work from abroad policy, 2-for-1 share purchase plans, an EV Scheme ...

like BentoML or equivalent. Familiarity with vector databases and retrieval pipelines for RAG architectures. Knowledge of cloud platforms (AWS, GCP, Azure) and MLOps tooling (MLflow, Kubeflow, or similar). Familiarity with voice‐to‐text, IVR, and/or computer vision systems is a plus. Strong understanding of software engineering best ...

containerisation (Docker, Kubernetes). Solid understanding of ML fundamentals (model training, evaluation, common architectures). Desired Skills (Bonus Points) Experience with MLOps tooling (MLflow, Kubeflow, Weights & Biases, or similar). Building data pipelines (real‐time or batch) using tools like Apache Spark, Kafka, Airflow, or dbt. Familiarity with recommender systems ...

lifecycle best practices Hands-on experience with ML libraries: PyTorch, PySpark, scikit-learn, Hugging Face Transformers Proficiency in AI tooling: Azure ML, Databricks, MLflow, LangChain, LangGraph Proven experience with Git, unit testing, containerisation and agile methodologies (Jira, Confluence) Good knowledge of generative AI, machine learning, deep learning or NLP Strong ...

Neptune, or Blazegraph. Experience with embeddings, vector databases, RAG, LLM-based enrichment, or knowledge graph completion. Experience with MLOps tools such as Docker, Kubernetes, MLflow, Weights & Biases, Airflow, or similar. Experience with AWS, GCP, or Azure. Experience in construction, architecture, BIM, building materials, technical product data, catalogues, standards, or compliance ...

Candidates should have strong experience in AI Engineering, MLOps and cloud-native AI platforms, alongside hands-on knowledge of technologies such as LangChain, LlamaIndex, MLflow, Kubernetes, Docker and CI/CD tooling. Applicants will ideally demonstrate: * Experience working in a major Consulting firm, and/or in industry * A strong ...

following areas: object detection, segmentation, OCR, tracking, image classification, or video analytics. Experience with ML Ops practices and tools such as Docker, Kubernetes, MLflow, and Weights & Biases. Systematic approach to model evaluation, benchmarking, data quality control, and error analysis. Familiarity with GPU/CPU inference optimization, latency management, and model ...

scikit-learn, NumPy, LightGBM, Pandas, LangChain/LangGraph, TensorFlow, etc.) PySpark AWS cloud infrastructure: EMR, ECS, Athena, etc MLOps/DevOps: Terraform, Docker, Airflow, MLFlow Monitoring and evaluation platforms including New Relic and Braintrust More information Enjoy fantastic perks like private healthcare & dental insurance, a generous work from abroad policy ...

risk management, and compliance (Zero Trust architectures, identity‐aware AI access, secrets management) AI/ML platforms, responsible AI practices, and model lifecycle management (MLflow, Vertex AI, SageMaker, Azure ML, Arize, Azure AI Studio) Design and operationalize enterprise‐scale GenAI and agent‐based solutions. Experience with modern AI architectures including ...

Face Solid understanding of machine learning fundamentals and performance evaluation techniques Experience working in cloud platforms (AWS, GCP, or Azure) with MLOps tools (e.g. MLflow, SageMaker, Vertex AI) Comfortable working independently and delivering high-quality work to tight timelines Experience working in fast-paced environments or scale-up settings Company ...

pipelines Build and maintain CI/CD pipelines for inference services, retrievers, ingestion workflows, and RAG components Implement observability across AI workloads using CloudWatch, MLflow, and OpenTelemetry - covering latency, throughput, cost, and system health Apply secure-by-design principles including IAM, encryption, network controls, and audit logging Work closely with ...

GraphQL APIs Cloud & Infra: AWS (ECS, S3, Lambda), Docker, Cloudformation, Pulumi, CI/CD with GitHub Actions ML/AI: PyTorch, TensorFlow, scikit‐learn, MLflow for experiment tracking, Zenml for ML pipelines Data: PostgreSQL, DynamoDB, data pipelines with Zenml (We’re open to evolving the stack and expect ...

hands-on practice in Python. Familiarity with popular machine learning libraries and frameworks such as scikit-learn, Hugging Face, PyTorch and TensorFlow. Experience with MLFlow, AWS SageMaker and Bedrock is preferred.Good written and oral communication skills, including the ability to communicate across business areas and increase overall knowledge across ...

experimentation and continuous learning. Mentor junior data scientists and contribute to knowledge sharing across the team. Technical Stack Core: Databricks Power BI REST APIs MLflow Hugging Face Transformers Microsoft Fabric Docker CI/CD with Azure DevOps Power Automate integration for AI workflows What You'll Bring Hands‐on experience ...

requirements and communicate findings effectively. Stay current with developments in AI and machine learning through continuous learning. Technical Stack Core: Power BI LangChain basics MLflow Databricks Hugging Face Transformers What You'll Bring Hands-on experience in data science or applied analytics. Solid Python programming skills and understanding of machine ...

site in our Alkmaar office Nice to Have (But Not Required) Experience deploying ML models into production environments Familiarity with MLOps tooling such as MLflow, CI/CD workflows, and model monitoring Experience with AWS, Azure, or GCP Understanding of real‐time systems, motion synthesis, or 3D graphics pipelines Experience ...

reviews. Desirable Experience Experience with Generative AI and Agentic AI. Experience designing or validating continuous monitoring frameworks for AI models. Experience with Azure Databricks, MLflow, Azure ML Services or similar platforms. Experience working within DevOps or MLOps environments. Experience with Docker and Kubernetes. Existing network within the UK AI, analytics ...

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 ...

financial or time-series data Experience building LLM/agent systems (prompting, retrieval, LangGraph, MCP, tool use) Familiarity with CI/CD, Terraform, MLflow, feature stores, vector databases and modern data governance practices Experience in commodities or financial trading environments, with understanding of market microstructure, fundamentals and risk, plus exposure ...

versioning, and retraining workflows.* Hands-on experience with model deployment and runtime management across varied environments (batch, real-time, REST, edge), using tools like MLflow, SageMaker, Databricks, or other equivalent.* Strong background in monitoring, observability, and incident response — including drift detection, fairness tracking, latency alerts, and recovery protocols.* Skilled ...

/FEA workflows generate and consume data Experience building model serving infrastructure with latency and throughput requirements Familiarity with experiment tracking tools (Weights & Biases, MLflow) and observability stacks (Prometheus, Grafana) What we offer Equity options – share in our success and growth. 10% employer pension contribution – invest in your future. Free ...

including Circadia’s clinical monitoring hardware, working with firmware and embedded engineering teams as needed. Manage model versioning, promotion, and rollback workflows through the MLflow model registry. Evaluate and implement strategies for safe model rollouts (e.g. shadow deployments, canary releases) as the platform matures. Experiment Tracking & Model Registry Maintain … improve the MLflow-based experiment tracking and model registry infrastructure. Establish conventions for experiment logging, artifact storage, model metadata, and lineage tracking. Enable ML engineers to move seamlessly from experimentation to production deployment with minimal friction. Data & Model Versioning Implement and maintain training data versioning and dataset management practices ...

researchers use to launch experiments, data jobs, and production endpoints — workflow engines (e.g., Kubeflow Pipelines, Airflow), GPU schedulers (e.g., Volcano, Slurm), experiment trackers (e.g., MLflow, Weights & Biases), and managed‐inference platforms (e.g., Modal, Triton) — and maintain a launcher SDK for one‐command runs. Containerization and packaging: Ship workloads with Docker … BigQuery, Snowflake), and embedded (e.g., SQLite) stores; and object storage with caching layers. Familiarity with ML workflow orchestration and experiment tracking (e.g., Kubeflow Pipelines, MLflow). Experience with monitoring and observability tooling (e.g., Prometheus/Grafana, OpenTelemetry) and CI/CD for infra and ML workflows (e.g., GitHub Actions). ...