1 to 25 of 40 Remote/Hybrid Amazon SageMaker Jobs in England

that fuel analytics, AI/ML, and data-driven operations.* Design and build high-performance data integration solutions: Use AWS Glue, AWS Step Functions, Amazon EventBridge, and AWS Database Migration Service (DMS) to orchestrate ingestion, transformation, and movement of data across on-premises and cloud sources into Amazon … Design and oversee the delivery of secure lakehouse and warehouse architectures: Implement logical and physical data models, data quality controls, and governance practices using Amazon S3 (data lake), AWS Lake Formation, Amazon Redshift, and Amazon Athena to ensure trusted data.* Ability to design AI/ML-enabled ...

experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/B testing methodology, and statistical evaluation Proven track record transitioning models ...

scaling AI solutions using at least one major cloud platform: Azure (Foundry, AI Studio, OpenAI, AKS), GCP (Vertex AI, Cloud Run), AWS (Bedrock, SageMaker)* Experience building and automating AI/ML pipelines using tools such as MLflow, Kubeflow, Azure ML, Vertex Pipelines, Airflow or Google ADK* Hands-on experience ...

lifecycle. What you’ll be doing Build and maintain ML pipelines for training, evaluation, and deployment using tools like Databricks, MLFlow, Airflow, DBT, Sagemaker, Tecton Support AI scientist creating reproducible, containerized model training environments (on-demand and scheduled), and manage compute at scale (e.g., spot/GPU autoscaling) Define ...

experience of building data pipelines using Spark, Python or SQL - Experience working with AWS and its data and AI/ML services such as SageMaker - Experience of big data and lakehouse platforms on AWS (EMR, Databricks or Snowflake) - Experience building data platforms such as Data Lakes, Lakehouses or Data ...

experience of building data pipelines using Spark, Python or SQL - Experience working with AWS and its data and AI/ML services such as SageMaker - Experience of big data and lakehouse platforms on AWS (EMR, Databricks or Snowflake) - Experience building data platforms such as Data Lakes, Lakehouses or Data ...

experience of building data pipelines using Spark, Python or SQL - Experience working with AWS and its data and AI/ML services such as SageMaker - Experience of big data and lakehouse platforms on AWS (EMR, Databricks or Snowflake) - Experience building data platforms such as Data Lakes, Lakehouses or Data ...

experience of building data pipelines using Spark, Python or SQL - Experience working with AWS and its data and AI/ML services such as SageMaker - Experience of big data and lakehouse platforms on AWS (EMR, Databricks or Snowflake) - Experience building data platforms such as Data Lakes, Lakehouses or Data ...

deploying ML models at scale using Docker, Kubernetes, or serverless Deep understanding of ML fundamentals: optimisation, regularisation, evaluation metrics Experience with cloud ML services (SageMaker, Vertex AI, or Azure ML) Strong software engineering practices: version control, testing, CI/CD MSc or PhD in Computer Science, Machine Learning ...

with serving patterns (e.g., REST APIs, batch inference, event-driven) Experience with orchestration tools (e.g., Airflow, Dagster) and cloud-native ML platforms (e.g., AWS SageMaker, GCP Vertex AI) Ability to influence decision-making regarding infrastructure and tooling, balancing 'build vs. buy' discussions Strong knowledge of Infrastructure as Code (Terraform ...

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 ...

Machine Learning, or a related technical discipline. Public writing, talks, or threads about building with AI. MLOpsand model serving experience (BentoML,MLflow, Vertex AI, SageMaker). Streaming and batch ingestion pipelines (Spark, Airflow, Beam, Glue). Healthcare or life sciences domain exposure. AWS Professional certification or other relevant industry ...

calibration)• Guardrail and AI-observability tooling (e.g. NeMo Guardrails, OpenTelemetry GenAI conventions, LangSmith, Braintrust)MLOps & LLMOps• Hands-on with MLOps platforms (Azure ML, Databricks, SageMaker) and vector/retrieval databases (Pinecone, Milvus, pgvector)• Experience with GPU-accelerated infrastructure and NVIDIA AI Enterprise or equivalent stacks• Exposure to fine-tuning ...

Terraform, Jenkins, Cloudformation or any other IAAC. Proven Experience building end-to-end systems as a Platform Engineer, ML DevOps Engineer on AWS Sagemaker and similar tools. Knowledge and experience with CI/CD tools. Strong hands-on technical skills in automation (Jenkins, GitLab, Docker, Kubernetes, Shell Scripting ...

tidyverse, caret, ggplot, etc.). Proven experience developing, refining, and monitoring NLP models. Familiarity with database management tools and techniques (e.g., SQL, Selenium, S3, Sagemaker, API protocols) is preferred but not required. Understanding model evaluation methods and metrics. Ability to operationalize non-technical ideas into relevant research designs, features ...

tidyverse, caret, ggplot, etc.). Proven experience developing, refining, and monitoring NLP models. Familiarity with database management tools and techniques (e.g., SQL, Selenium, S3, Sagemaker, API protocols) is preferred but not required. Understanding model evaluation methods and metrics. Ability to operationalize non-technical ideas into relevant research designs, features ...

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 ...

statements and figure out how to solve them Some extra skills that are great (but not essential): Experience with MLOps tools: Airflow, MLflow, AWS SageMaker, AWS S3, AWS EMR, CI/CD Prior experience in the fraud domain and a strong understanding of fraud detection techniques Experience designing ...

Strong Generative AI architecture experience, including LLM hosting, RAG, vector databases, prompt orchestration and guardrails. Knowledge of AI platform tooling such as Azure ML, Amazon SageMaker, MLflow, Kubeflow and Databricks . Ability to evaluate technologies and make evidence-based architectural decisions. Experience designing secure, scalable and cost-optimised ...

code, not just notebooks.* Hands-on experience with Snowflake (or a comparable cloud data warehouse — BigQuery, Redshift, Databricks).* Experience deploying models on AWS (SageMaker, Lambda, ECS, or similar).* Solid grounding in statistics, experimentation, and causal inference — you know when a correlation isn't enough.* Track record ...

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 ...

cloud platform, and debugging from logs and traces. Nice to have Agents used daily by operators, with a feedback loop. AWS SageMaker, AWS ECS/Fargate, Terraform and CircleCI. Snowflake and dbt. Event logging for analytics or machine learning. Lead generation or ad tech. How you'll work Commercial ...

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. ...

business-critical services. - GitLab, PostgreSQL, NGINX, VPN/OpenVPN, Elastic/Kibana and Windows administration. Desirable - C#, .NET, JavaScript, React, Vue.js and microservices. - AWS SageMaker, AI/LLM integrations and Python-based analytics tooling. - Enterprise cloud architecture and secure-by-design principles. - Disaster recovery and business continuity planning. - Experience ...

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 ...