1 to 25 of 34 MLflow Jobs in London

data quality for machine learning applications. Machine Learning Operations (MLOps) - Experience deploying ML models to production environments using containerisation (Docker), orchestration (Kubernetes), model versioning (MLflow, DVC), monitoring model performance and drift, A/B testing frameworks, and implementing CI/CD pipelines for automated model training and deployment. Understanding ...

data quality for machine learning applications. Machine Learning Operations (MLOps) - Experience deploying ML models to production environments using containerisation (Docker), orchestration (Kubernetes), model versioning (MLflow, DVC), monitoring model performance and drift, A/B testing frameworks, and implementing CI/CD pipelines for automated model training and deployment. Understanding ...

Data Manipulation (SQL, Pandas, Pyspark) Azure AI (Azure AI Foundry, AI Search, Document Intelligence, AI Services) Data Science & Machine Learning (Databricks, Python, SKLearn, XGBoost, MLFlow, EDA) Familiarity with LLMs (OpenAI, Prompt Engineering, LangChain) Relevant Azure Data & Computation services (ADLS, ADF, Databricks, SQL Databases) Supporting: Azure ML Services React/ ...

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 ...

scalable AI deployment. Use AI-powered dev tools like GitHub Copilot, Cursor, and Codeium to speed up iteration. Apply MLOps/LLMOps practices with MLflow, Weights & Biases, and Kubeflow. ?? Youll Bring Strong Python skills and experience with LangChain, Transformers, Hugging Face. Solid grasp of LLM behavior, prompt optimization, and data ...

clearly to non-technical stakeholders Technical skills (a big plus): Knowledge of deep learning frameworks (PyTorch, TensorFlow), transformers, or LLMs Familiarity with MLOps tools (MLflow, SageMaker, Airflow, etc.) Experience with streaming data (Kafka, Kinesis) and distributed computing (Spark, Dask) Skills in data visualization apps (Streamlit, Dash) and dashboarding (Tableau, Looker ...

Proficiency in Python and familiarity with ML libraries like scikit-learn, XGBoost, PyTorch or TensorFlow. Experience with ML Ops tools and practices such as MLflow, model registries, containerisation (Docker/Kubernetes), and CI/CD pipelines. Comfortable working with cloud platforms (preferably Azure) and distributed computing environments (e.g., Spark, Databricks ...

scalable, maintainable, and production-ready AI systems. Proficiency in Python with AI/ML frameworks (PyTorch, TensorFlow). Experience with MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes). Deep proficiency in Python and extensive experience with relevant AI/ML/NLP libraries (e.g., Hugging Face Transformers, spaCy, NLTK ...

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 ...

models in production environments. Knowledge of distributed training, GPU/TPU optimisation, 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 ...

hands-on experience building and deploying production-grade AI or ML-enabled systems. Deep understanding of modern cloud and MLOps environments (AWS, Azure, GCP; MLflow, SageMaker, or equivalent). Proficiency in at least one major programming language (Python preferred) and modern software delivery practices (CI/CD, containers, orchestration). ...

process. Strong knowledge of big data tool such as Spark, Databricks and Python. Strong understanding of common machine learning techniques and frameworks (e.g. mlflow). Strong knowledge of Natural language processing (NPL) concepts. Strong knowledge of scrum practices and agile mindset. Skills & Core competences Strong Analytical and Problem-Solving Skills ...

Airflow, dbt, Databricks, Snowflake, etc. GitHub, Azure DevOps and related developer tooling and CI/CD platforms, Terraform or other Infra-as-Code MLflow, AzureML or similar for MLOps; LangSmith, Langfuse and similar for LLMOps The difference to our "AI Engineer" role is: Do you "use/consume" these technologies ...

deploying cutting-edge machine learning solutions across the company.If you enjoy end-to-end ownership (from experimentation to deployment), working with AWS, Docker, MLflow, TensorFlow/PyTorch, and contributing to innovative projects with a flexible, results-focused culture, this could be an exciting match. Skills: Ability to write and produce ...

Strong design and development skills using Python. Python's libraries for machine learning: PySpark, Pytorch, scikit-learn and pandas. Technical experience using Databricks and MLFlow (Other Platforms can be considered). Good understanding of software code review standards - CI/CD. Stochastic Simulation modelling experience. If you are interested ...

Strong design and development skills using Python. Python's libraries for machine learning: PySpark, Pytorch, scikit-learn and pandas. Technical experience using Databricks and MLFlow (Other Platforms can be considered). Good understanding of software code review standards - CI/CD. Stochastic Simulation modelling experience. If you are interested ...

library skills Hands-on experience with GenAI APIs and production deployments Knowledge of the full ML lifecycle and MLOps tools such as MLflow or SageMaker Strong communication skills and experience working with senior stakeholders A grounding in statistics and an agile, problem solving mindset Some Scala exposure is a bonus ...

library skills Hands-on experience with GenAI APIs and production deployments Knowledge of the full ML lifecycle and MLOps tools such as MLflow or SageMaker Strong communication skills and experience working with senior stakeholders A grounding in statistics and an agile, problem solving mindset Some Scala exposure is a bonus ...

Nice-to-Have Alongside the essential prerequisites, we're excited to find experience in version control of data and artefacts (like DeltaLake, DVC, or MLFlow), designing and operating cloud-based systems, preferably within AWS or Databricks, familiarity with messaging platforms and proficiency in infrastructure as code (e.g. Terraform, CloudFormation, Pulumi ...

feeds, trade lifecycle, and financial data models. Expertise with modern data technologies (ClickHouse, PostgreSQL, Kafka, or equivalents.). Experience implementing ML Ops frameworks (e.g. MLflow, Kubeflow, Prefect, or SageMaker) Deep understanding of ETL/ELT pipelines, streaming architectures, and data lifecycle management. Experience working in Kubernetes and cloud-native environments ...

feeds, trade lifecycle, and financial data models. Expertise with modern data technologies (ClickHouse, PostgreSQL, Kafka, or equivalents.). Experience implementing ML Ops frameworks (e.g. MLflow, Kubeflow, Prefect, or SageMaker) Deep understanding of ETL/ELT pipelines, streaming architectures, and data lifecycle management. Experience working in Kubernetes and cloud-native environments ...

brand estate with high stakeholder visibility Coach teams, guide decisions, and bring structure to an ambiguous environment Key Skills AWS SageMaker (essential) Snowflake GitLab MLflow AWS Bedrock (bonus) Soft Skills Thrives in ambiguity Able to navigate political landscapes and conflicting priorities Strong communicator with the ability to explain ML concepts ...

brand estate with high stakeholder visibility Coach teams, guide decisions, and bring structure to an ambiguous environment Key Skills AWS SageMaker (essential) Snowflake GitLab MLflow AWS Bedrock (bonus) Soft Skills Thrives in ambiguity Able to navigate political landscapes and conflicting priorities Strong communicator with the ability to explain ML concepts ...

Milvus, ChromaDB, pgVector) and embedding stores. UseAI-powered dev tools(GitHub Copilot, Cursor, Codeium, Aider, Windsurf) to accelerate iteration. ImplementLLMOps/PromptOpsusing: Weights & Biases,MLflow,LangSmith,LangFuse,PromptLayer,Humanloop,Helicone,Arize Phoenix Benchmark and evaluate LLM systems usingRagas,DeepEval and structured evaluation suites. Deployment & Infrastructure Containerize and deploy workloads withDocker … Gemini 2.x, Mistral Large, LLaMA 3, Cohere Command R+, DeepSeek Frameworks: LangChain, LlamaIndex, Haystack, AutoGen, CrewAI Tools: GitHub Copilot, Cursor, LangSmith, LangFuse, Weights & Biases, MLflow, Humanloop Cloud: Azure ML, AWS SageMaker, Google Vertex AI, Databricks, Modal Infra: Python, Docker, Kubernetes, SQL/NoSQL, PyTorch, FastAPI, Redis ...

LangChain, LangGraph, or custom). Create and maintain data pipelines (Airflow, dbt, Step Functions). Implement monitoring, observability, and automated retraining (CloudWatch, Prometheus, Grafana, MLflow). Embed strong security, compliance, and guardrail practices across all ML workflows. Mentor junior engineers and promote engineering best practices. Key Requirements Essential 3+ years … SageMaker, EKS/Fargate, Lambda, Step Functions, S3). Proficient with Docker, Kubernetes , and IaC (Terraform or AWS CDK). Experience with MLflow , CI/CD tools, and automated testing. Hands-on with LLM deployment and multi-agent systems . Proven experience building data pipelines and production ML workflows. Strong ...