20 of 20 Permanent Amazon SageMaker Jobs in London

. Strong experience with data manipulation and pipelines using Pandas, NumPy, and SQL. Knowledge of containerized deployments (Docker, Kubernetes) and cloud ML services (AWS SageMaker, GCP Vertex AI, or Azure ML) preferred. Excellent problem-solving skills, eagerness to learn, and ability to thrive in a fast-paced, evolving environment. ...

experience with ML frameworks (PyTorch, TensorFlow, Scikit-learn). Is experienced with cloud platforms (ideally GCP: BigQuery, Vertex AI, Dataflow), but AWS/SageMaker or similar is also valued. Has operated in distributed computing environments, working with large datasets and parallelized processing. Can communicate technical concepts and trade-offs ...

vector databases (Pinecone, Weaviate, OpenSearch), or multi-agent orchestration. Experience building conversational agents or AI-driven automation systems. Knowledge of MLOps tooling such as SageMaker, MLflow, or Databricks. Familiarity with RLHF, alignment techniques, or model interpret ability. Interest in consumer behaviour, research methodologies, or product decision-making. Startup experience ...

production environments. Strong Python skills, with experience in frameworks like PyTorch, TensorFlow, or Hugging Face. Confident working in AWS or similar cloud environments (SageMaker, Lambda, Docker, etc.). Experienced in (or eager to explore) areas such as forecasting, optimisation, reinforcement learning, generative AI, or computer vision. Solid engineering mindset ...

effort and costs Nice to have * CI/CD experience (Azure DevOps, GitHub Actions, Jenkins)* Exposure to ML Ops tooling (Azure ML, AI Foundry, SageMaker or Vertex AI)* Infrastructure-as-Code (Bicep, ARM, Terraform)* Previous work building Gen AI-powered products or automation Tech environment you'll be joining ...

Hands-on ownership of CI/CD (Jenkins/Azure DevOps/GitHub Actions) and MLOps in Azure ML/Azure AI Foundry/SageMaker/Vertex AI. Working knowledge of Infrastructure as Code (Bicep, ARM, Terraform). A test-driven development mindset and commitment to engineering quality. Broad ...

brightest minds and friendliest people in the industry! You work with some of the best tech in the industry, such as AWS SageMaker for ML, DBT for data processing along with standard analytical tools like Python, Redshift, Tableau etc. You gain hands-on exposure to an advanced Expected Credit ...

performance, suitability, training needs, and deployment approaches. Practical hands-on experience with at least two hyperscaler AI platforms , such as: AWS Bedrock/SageMaker Google Vertex AI OpenAI Azure ML Solid understanding of statistics, machine learning, data science fundamentals, data engineering, and big data concepts. Knowledge of the process ...

Architect Proven experience with LLMs/SLMs , model evaluation, performance tuning and deployment Hands-on experience with at least two: AWS Bedrock/SageMaker , Google Vertex AI , Azure ML , OpenAI Strong grounding in statistics, ML, data engineering and big data concepts Ability to simplify complexity and guide non-technical ...

expertise in one or more of the following: NoSQL databases (e.g., DocumentDB, MongoDB) RDF/graph technologies (e.g., GraphDB) AI/ML platforms (e.g., SageMaker, Bedrock) Search technologies (e.g., Solr, OpenSearch, Elasticsearch) Cloud-based data pipeline engineering (AWS) Produce clean, testable, maintainable code that supports incremental innovation. Build ...

expertise in one or more of the following: NoSQL databases (e.g., DocumentDB, MongoDB) RDF/graph technologies (e.g., GraphDB) AI/ML platforms (e.g., SageMaker, Bedrock) Search technologies (e.g., Solr, OpenSearch, Elasticsearch) Cloud-based data pipeline engineering (AWS) Produce clean, testable, maintainable code that supports incremental innovation. Build ...

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 (AWS preferred). ...

software solutions. • Expertise in AI Model Architecture – LLMs, SLMs, performance, training, deployment. • Hands-on experience with at least two hyperscaler platforms: AWS Bedrock/SageMaker, Google Vertex AI, Azure ML, OpenAI. • Strong understanding of statistics, machine learning, data science, and big data. • Knowledge of cloud security, landing zones ...

scale data analytics (e.g. Spark/PySpark) Experience in writing, testing and implementing scripts (e.g. Python, Scala) Experience of cloud data stack use (e.g. SageMaker Notebooks, S3, Glue, Athena) Communicating technical concepts clearly to both technical and non-technical stakeholders using appropriate language and methods. Profiling data and analysing ...

large-scale analytics engines (e.g. Spark/PySpark) and scripting languages such as Python or Scala. Hands-on use of cloud data stacks (e.g. SageMaker Notebooks, S3, Glue, Athena) and modern storage formats or frameworks (e.g. Parquet, Delta Lake, Fabric). Experience with DevOps/DataOps tooling and practices ...

large-scale analytics engines (e.g. Spark/PySpark) and scripting languages such as Python or Scala. Hands-on use of cloud data stacks (e.g. SageMaker Notebooks, S3, Glue, Athena) and modern storage formats or frameworks (e.g. Parquet, Delta Lake, Fabric). Experience with DevOps/DataOps tooling and practices ...

pipelines operating on challenging datasets, delivering reliable, scalable, and observable solutions. What you’ll do Deploy ML and LLM models into AWS production environments (SageMaker, Bedrock, Lambda, ECS, API Gateway) Design and maintain scalable data pipelines for training, validation, deployment, and monitoring Ensure data quality and reliability across multiple … production ML workflows Must-have Senior experience deploying ML or LLM models in production Strong Python engineering skills (FastAPI or similar frameworks) AWS experience: SageMaker, Lambda, ECS, or serverless pipelines Comfortable working with complex datasets and robust data pipelines CI/CD, monitoring, and observability for ML pipelines Strong ...

help shape best practices in security, automation, and cost-efficient AI deployment. Key Responsibilities Architect secure, scalable ML and GenAI systems using AWS services (SageMaker, EKS/Fargate, Lambda, Step Functions). Build CI/CD pipelines for ML models, agents, and GenAI applications. Deploy LLMs and orchestrate multi … junior engineers and promote engineering best practices. Key Requirements Essential 3+ years experience in MLOps/ML Engineering/AIOps. Strong expertise in AWS (SageMaker, EKS/Fargate, Lambda, Step Functions, S3). Proficient with Docker, Kubernetes , and IaC (Terraform or AWS CDK). Experience with MLflow , CI/ ...

Language Models) performance, suitability, training requirements, and deployment Cloud & Hyperscalers – Practical experience with at least two of the following is required: AWS Bedrock/Sagemaker, Google Vertex AI, OpenAI and Azure ML is required An understanding of underlying statistics, machine learning and data science, data engineering and big data … qualified virtual GP; six volunteering days a year and much more. Required Skills Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, Agile Methodology, Amazon Web Services (AWS), Analytical Thinking, Business Architecture, Business Continuity, Business Process Modeling, Business Process Workflow, Coaching and Feedback, Communication, Creativity, Embracing Change, Emotional Regulation, Empathy ...

Language Models) performance, suitability, training requirements, and deployment Cloud & Hyperscalers – Practical experience with at least two of the following is required: AWS Bedrock/Sagemaker, Google Vertex AI, OpenAI and Azure ML is required An understanding of underlying statistics, machine learning and data science, data engineering and big data … qualified virtual GP; six volunteering days a year and much more. Required Skills Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, Agile Methodology, Amazon Web Services (AWS), Analytical Thinking, Business Architecture, Business Continuity, Business Process Modeling, Business Process Workflow, Coaching and Feedback, Communication, Creativity, Embracing Change, Emotional Regulation, Empathy ...