51 to 75 of 142 Amazon SageMaker Jobs in London

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 infrastructure, and vector ...

everything that gets those models in front of a customer and keeps them running: the training and deployment infrastructure on AWS and SageMaker, reproducible and configuration‐driven training runs, environments defined in code, release pipelines that make a deployment routine rather than an event, and the monitoring that tells … machine learning engineers/scientists and turn them into production services that meet our latency, cost and reliability targets. Build and maintain SageMaker training, processing and inference workloads, and the pipelines that orchestrate them. Make training runs reproducible and configuration‐driven, so any result can be rebuilt from code. ...

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 No conditions specified #J ...

e.g., seaborn) Proficient in working with cloud platforms (AWS preferred), code versioning (Git), experiment tracking (e.g., MLflow) Experience with cloud‐based ML tools (e.g., SageMaker), data and model versioning (e.g., DVC), CI/CD (e.g., GitHub Actions), workflow orchestration (e.g., Airflow/Dagster) and containerised solutions (e.g., Docker ...

iterative engineering environment.Experience deploying and managing machine learning model deployments (MLOps) on appropriate services. Examples include (but not limited to) Azure Machine Learning, AWS Sagemaker, Databricks or Snowflake.Experience using AI or Agentic techniques in application of the role through GitHub CoPilot, Claude Code, or equivalent.A drive for self-improvement ...

Python, Java, etc) in support of Investment Portfolio Management and Construction Utilizing AWS technologies such as Lambda, API Gateway, DynamoDB, S3, Glue, Redshift, EMR, Sagemaker, EKS/ECS. Working in a team with experienced software engineers to identify great projects and features that will help you grow in your ...

Tableau would be beneficial but is not essential. Our Tech Environment: Data Stack: Snowflake, dbt, SQL, Python, Fivetran, Dagster, DataDog, Tableau. Infrastructure: AWS (SageMaker, EC2, Lambda, Glue, S3), Terraform, API Gateway. Collaboration Tools: GitHub, Jira, Confluence. Analytics Tools: GA4, GTM, GCP BigQuery. How we get there: Recruiter Screening Call ...

Familiarity with cloud‐based application development (AWS & Azure). Familiarity with one or more ML frameworks and technologies: scikit‐learn, xgboost, TensorFlow, PyTorch, Spark, SageMaker, Vertex AI, Kubeflow, Seldon, Triton. Strong communication skills, able to express ideas clearly and collaborate across teams. #J-18808-Ljbffr ...

person other engineers look to on the harder architectural calls. Tech stack Snowflake, dbt, SQL, Python Fivetran, Dagster, DataDog, Tableau AWS (SageMaker, EC2, Lambda, Glue, S3), Terraform, API Gateway GitHub, Jira, Confluence What we're looking for Advanced SQL, genuinely at the top end for complex modelling and performance ...

ethicsAn understanding of data safety in use of Large Language ModelsKnowledge and experience of either AWS or Azure:AWS (boto3, Bedrock, Sagemaker, Lambda, S3, EC2)Azure (azure Open AI service, Cosmos DB)PythonLangGraphNeo4j/cypherOther coding languages/frameworks e.g. Java/.NetAI RAG (retrieval augmented generation)Graph RAGFew ...

Technical Knowledge: Strong understanding of modern AI/ML technologies and cloud-based solutions. Tools & Platforms: Familiarity with Snowflake, Databricks, Azure AI Foundry , AWS SageMaker, and other leading platforms. Data Science Expertise: Knowledge of data science fundamentals, solution lifecycles, and MLOps methodology. Generative AI Knowledge: Experience with LLMs, neural ...

experience in using one of 3 major cloud technologies (AWS, Azure or GCP) in a production environment, as well as ML platforms (e.g., AWS Sagemaker, Azure Machine Learning studio) Be a ‘lifelong learner’ and can demonstrate a drive to always be learning and developing your skillsets and develop ...

enhance your day-to-day work. Technologies and Tools Python Machine learning frameworks (e.g. PyTorch, TensorFlow, scikit-learn) ML/MLOps tooling (e.g. SageMaker, MLflow, TFServing) Spark and Databricks AWS services (e.g. IAM, S3, Redis, ECS) CI/CD tooling and best practices Streaming and batch data systems (e.g. ...

honesty. Nice to have: Knowledge of R or other programming languages Knowledge of current UK AI/ML compliance and regulation. Experience with AWS Sagemaker Experience with Snowflake Experience with Databricks What will you get in return Everyone’s different. That’s why at Zurich, we offer a wide ...

Python, applied AI, Generative AI, prompt engineering, retrieval-augmented generation (RAG), vector stores, and agentic architectures. Hands-on familiarity with platforms like Databricks, Snowflake, SageMaker, or Vertex. Agent lifecycle management, observability, and governance frameworks.Agentforce & Salesforce Platform Deep architectural understanding of how Data and AI are activated within Salesforce — including ...

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 … Model Context Protocol (MCP). Hands‐on experience with or solid understanding of Amazon Web Services (AWS). Understanding of cloud architecture and the software development lifecycle. Experience coaching and mentoring other product managers and setting a high bar for execution. Experience operating at scale in highly available, secure ...

Strong Python (pandas, scikit-learn, PyTorch) and SQL Solid grounding in statistics, experimentation and causal inference Experience with at least one MLOps stack (MLflow, SageMaker, Vertex) Nice to have Published research or Kaggle competition experience Domain depth in financial services, retail or healthcare Send your CV and a short ...

cloud security for services and infrastructure. Experience with Kubernetes (K8S) is a plus. Cloud Expertise: Familiarity with AI infrastructure on AWS and GCP, including Sagemaker, Vertex, Triton, and GPU computing. Bonus Points: Experience with Airbyte is a significant advantage. Perks and Benefits: Fully Remote: Freedom to work from anywhere ...

Infrastructure monitoring and alerting Performance monitoring Log analysis and troubleshooting Service availability monitoring Root cause analysis Desirable skills and experience Cloud & Platform Technologies AWS SageMaker Python scripting and automation Container orchestration platforms Infrastructure security and hardening Cloud networking and connectivity Application Support Knowledge C# .NET JavaScript React REST APIs ...

Infrastructure monitoring and alerting Performance monitoring Log analysis and troubleshooting Service availability monitoring Root cause analysis Desirable skills and experience Cloud & Platform Technologies AWS SageMaker Python scripting and automation Container orchestration platforms Infrastructure security and hardening Cloud networking and connectivity Application Support Knowledge C# .NET JavaScript React REST APIs ...

Cloud-based application development (we use AWS & Azure)Familiarity with one or more ML frameworks and technologies: scikit-learn, xgboost, TensorFlow, PyTorch, Spark, SageMaker, Vertex AI, Kubeflow, Seldon, TritonStrong communication skills, able to express ideas clearly and collaborate across teamsAdditional InformationBring all of you to workWe create the conditions ...

implementing privacy-first techniques like differential privacy or secure data handling.Familiarity with infrastructure-as-code tools like Terraform, Kubernetes, or MLOps platforms such as SageMaker or Vertex AI.Hands-on experience fine-tuning LLMs, prompt engineering, or managing the latency and cost trade-offs of large language models at scale.What ...

another businesses where price, demand and inventory interact dynamically. Snowflake and AWS experience, with exposure to AI or model-serving environments such as SageMaker or Snowflake Cortex. Customer data platforms, identity resolution, consent management, experimentation or feedback-loop design. Our client can offer a salary in the region ...

another businesses where price, demand and inventory interact dynamically. Snowflake and AWS experience, with exposure to AI or model-serving environments such as SageMaker or Snowflake Cortex. Customer data platforms, identity resolution, consent management, experimentation or feedback-loop design. Our client can offer a salary in the region ...

another businesses where price, demand and inventory interact dynamically. Snowflake and AWS experience, with exposure to AI or model-serving environments such as SageMaker or Snowflake Cortex. Customer data platforms, identity resolution, consent management, experimentation or feedback-loop design. Our client can offer a salary in the region ...