26 to 50 of 137 Amazon SageMaker Jobs in England

data engineering development experience You may have experience with the following tools: AWS data tooling such as S3/Glue/Redshift/SageMaker (Or relevant experience in another cloud technology). Specific tooling - Databricks Strong Data related programming skills SQL/Python/Spark Experience of industrialising ...

Expertise with modern data platforms (e.g., BigQuery/Databricks) and data processing workflows (ETL, pipelines). Excellent experience with cloud hosted AI platforms (Bedrock, Sagemaker, VertexAI) Strong problem-solving abilities, with the capacity to learn quickly and adapt in a fast-paced environment. Excellent communication and a drive ...

production deployment, including MLOps, monitoring and drift detection. Practical knowledge of ML frameworks (e.g. scikit-learn, PyTorch, XGBoost) and cloud-native ML services (SageMaker, Azure ML, Vertex AI). Software Engineering: Production-grade Python services (FastAPI, AWS Lambda, event-driven patterns) and front-end development with React/Next.js ...

production deployment, including MLOps, monitoring and drift detection. Practical knowledge of ML frameworks (e.g. scikit-learn, PyTorch, XGBoost) and cloud-native ML services (SageMaker, Azure ML, Vertex AI). Software Engineering: Production-grade Python services (FastAPI, AWS Lambda, event-driven patterns) and front-end development with React/Next.js ...

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. ...

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. … PyTorch experience (TensorFlow also welcome) and the surrounding ecosystem: Hugging Face Transformers, timm, scikit‐learn, NumPy, pandas, OpenCV. Production experience on AWS, specifically Amazon SageMaker: training and processing jobs, pipelines, model registry, endpoints. Practical MLOps: experiment tracking and model versioning with MLflow, hyperparameter optimisation, and reproducible, configuration‐driven ...

Turn machine learning engineer/scientist models into production services meeting latency, cost, and reliability targets • Build and maintain SageMaker training, processing, and inference workloads • Build pipelines that orchestrate SageMaker workloads • Make training runs reproducible and configuration-driven so results can be rebuilt from code • Build monitoring … Deep hands-on PyTorch experience; TensorFlow welcome Experience with Hugging Face Transformers, timm, scikit-learn, NumPy, pandas, and OpenCV Production experience on AWS, specifically Amazon SageMaker, including training and processing jobs, pipelines, model registry, and endpoints Practical MLOps experience with MLflow, hyperparameter optimisation, and reproducible, configuration-driven training ...

with Cloud services, Infrastructure as Code (IaC) and containerized application development Familiarity with relational databases (e.g., Postgres) and AWS services such as S3, EKS, SageMaker, and Bedrock Practical experience with Kubernetes, EKS, Docker, Kafka, MLOps and Large Language Model Operations (LLMOps) Experience working on AIML systems and/ ...

practices to confirm they catch degradation before it costs the business.You'll assess CI/CD and deployment controls — Docker, Jenkins, and the AWS SageMaker, S3, Athena, and Lambda environments models run in.You'll evaluate model governance documentation, explainability approaches, and compliance with regulatory expectations on model risk, fairness ...

prompt optimization frameworks (AutoPrompt, DSPy) and building evaluation suites. Hands‐on experience with agentic frameworks (LangChain, LangGraph). Experience with AWS AI deployment services (SageMaker, Bedrock) and workflow orchestration. Demonstrated experience in financial services, particularly investment banking operations. Equal Opportunity Employer We recognize that our people are our strength ...

frameworks and data science packages such as PyTorch, TensorFlow, scikit‐learn, NumPy, pandas, SciPy, and statsmodels Experience deploying to AWS, including services such as SageMaker and Bedrock, and operating production large language model and machine learning workloads with attention to cost, latency, performance, security, and scaling Experience integrating human ...

Experience Proven experience designing and deploying production-grade AI/ML or LLM systems . Expertise with AWS or Azure AI services (e.g., Bedrock, SageMaker, OpenAI, Cognitive Services). Strong Python programming skills with hands‐on experience using frameworks like Autogen and LangGraph . Solid grounding in MLOps , containerisation ...

with prompt optimization frameworks (AutoPrompt, DSPy) and building evaluation suites. Hands-on experience with agentic frameworks (LangChain, LangGraph).Experience with AWS AI deployment services (SageMaker, Bedrock) and workflow orchestration. Demonstrated experience in financial services, particularly investment banking operations. Join us to help shape the future of Market Operations through ...

prompt optimization frameworks (AutoPrompt, DSPy) and building evaluation suites. Hands-on experience with agentic frameworks (LangChain, LangGraph). Experience with AWS AI deployment services (SageMaker, Bedrock) and workflow orchestration. Demonstrated experience in financial services, particularly investment banking operations. Join us to help shape the future of Market Operations through ...

Bedrock Experience with Kubernetes, CI or CD, infrastructure as code, and automation tools Familiarity with AI or ML platforms such as Databricks, SageMaker, or MLflow Exposure to hybrid cloud architectures and large scale data processing ecosystems Knowledge of enterprise data platforms, observability, and cost management tooling Leadership Expectations ...

frameworks and data science packages such as PyTorch, TensorFlow, scikit-learn, NumPy, pandas, SciPy, and statsmodels Experience deploying to AWS, including services such as SageMaker and Bedrock, and operating production large language model and machine learning workloads with attention to cost, latency, performance, security, and scaling Experience integrating human ...

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. ...

production Strong Python development skills Hands-on experience with LangGraph, LangChain, LlamaIndex, CrewAI or similar Experience with AWS, particularly Bedrock, Lambda, ECS, EKS or SageMaker Strong understanding of RAG, agentic AI and multi-agent architectures Experience with CI/CD, cloud infrastructure and application deployment Comfortable working directly with ...

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 ...

data, software, or machine learning-focused pipelines, with an understanding of monitoring, reliability, security, and operational support. DESIRABLE Experience with AWS services such as SageMaker, S3, EC2, Lambda, IAM, VPC, KMS, or Bedrock. Experience developing or contributing to scalable architectures for data-driven products or services. Experience working with ...

Infrastructure‐as‐code) tools like Terraform or CloudFormation in a production environment. Previous exposure to additional technologies like Seldon, KServe, RayServe, Kubernetes, MLFlow, Sagemaker, Kubeflow, Anyscale, Valohai, ArgoCD, Docker, Python, Java, Ray, Spark, Pandas, Argo Workflow, Postgres, Snowflake and BigQuery is highly desirable. Good to have: previous knowledge managing ...

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 ...

infrastructure security, reliability and operational best practice. Desirable Experience The following would be advantageous: MLOps or LLMOps experience. Experience with platforms such as SageMaker, Kubeflow or ZenML . Extensive on-premises Kubernetes deployment experience. Prometheus or comparable observability platforms. AWS Karpenter. AWS Compute Optimizer. Experience operating highly distributed systems. ...