26 to 50 of 142 Amazon SageMaker Jobs in London

Awareness of ethical, privacy, security and policy considerations in applied AI Desirable Experience Hands-on experience with AWS services such as Lambda, ECS, S3, SageMaker or Bedrock Knowledge of ML engineering and MLOps practices (e.g. Docker, MLflow) Experience working in government, defence or other highly regulated environments Proven application ...

Kubernetes).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 to work ...

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 ...

Kubernetes).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/ ...

robust scientific workAwareness of ethical, privacy, security and policy considerations in applied AIDesirable ExperienceHands-on experience with AWS services such as Lambda, ECS, S3, SageMaker or BedrockKnowledge of ML engineering and MLOps practices (e.g. Docker, MLflow)Experience working in government, defence or other highly regulated environmentsProven application of large ...

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 ...

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 ...

equivalents in Azure or GCP), with hands‐on work across classical ML and modern LLM/RAG systems using services like Amazon SageMaker and Bedrock. What you’ll doPartner with stakeholders across the business to explore high‐impact opportunities.Own the full lifecycle: problem framing, data discovery, feature engineering … methods, and building RAG systems.Orchestration: for example LangChain for pipelines/agents. RAG best practices and evaluation workflows (e.g., agentic/RAG patterns on SageMaker). Comfortable choosing the right technique for the job (from baselines to advanced models), with an emphasis on measurable impact and maintainability.Clear communication with ...

Tableau, Power BI) Infrastructure as Code experience (Terraform/CloudFormation) Industry experience relevant to your business Exposure to streaming data (Kinesis) or ML pipelines (SageMaker) experince in financial domain OtherLanguages English: C2 Proficient Seniority Senior London, United Kingdom of Great Britain and Northern Ireland Req. VR-124688 Strategy & Design ...

strong positive signal. Hands-on production experience with graph neural networks, anomaly detection, or behavioural biometrics, beyond prototyping or fine-tuning. Familiarity with AWS (SageMaker, Lambda, S3, Athena) and CI/CD practices. Experience mentoring or technically guiding other data scientists. Please include a CV in English. Curious ...

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 ...

Familiarity 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 innovative ...

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 ...

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

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 ...

learning frameworks and data science packages such as PyTorch, TensorFlow, scikit-learn, NumPy, pandas, SciPy, and statsmodelsExperience 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 scalingExperience integrating human ...