25 of 25 Amazon SageMaker Jobs in the City of London

ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js DevOps & Cloud: CI/CD, Docker, AWS (S3, Lambda, SageMaker), Kubernetes, Terraform/CDK ML Ops & Automation: MLFlow, feature stores, model monitoring, A/B testing Data Security & Compliance: Secure SDLC, ISO/NIST ...

/ML frameworks (PyTorch, TensorFlow). Prompt Engineering, Langchain, Langsmith/Langfuse, Gen AI/Agentic AI, Cloud platforms (Azure AI Foundry, AWS Sagemaker/Bedrock, GCP Vertex AI), MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes). Preferred Delivered AI projects within Agile frameworks Experience on Model Feedback ...

Security Clearance and willing to undergo the process Desirable experience Practical knowledge of AWS services such as Lambda, ECS, Bedrock, S3 or SageMaker MLOps and ML engineering tooling (e.g. Docker, MLflow) Experience working in highly regulated or government environments Track record of applying large language models to solve real ...

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, and statistical evaluation. Proven track record transitioning models from ...

Some Of These, But If Not We’ll Help You With Them • Good knowledge of AWS cloud services (e.g. Lambda, ECS, Bedrock, S3, Sagemaker) • ML Engineering and MLOps knowledge (e.g. Docker, ML flow) • Experience working with government or other carefully regulated industries • Track record of applying LLMs to robustly ...

technical concepts to diverse audiences. Eligible for DV security clearance; sponsorship cannot be provided. Desirable: Knowledge of AWS services (e.g., Lambda, ECS, Bedrock, S3, SageMaker). Experience with ML engineering and MLOps (e.g., Docker, MLflow). Experience in regulated industries or government-related projects. Applying LLMs or advanced ...

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 ...

TensorFlow Experience designing and delivering ML solutions across the full lifecycle, from experimentation to production Strong knowledge of AWS-based ML services (e.g. SageMaker, Lambda, S3) in production environments Experience with experiment design, hypothesis testing, A/B testing and statistical evaluation Proven ability to transition validated models into ...

have: Strong Python ML experience (e.g. scikit-learn, XGBoost, PyTorch, or TensorFlow) Production experience with AWS ML services (e.g. SageMaker, Lambda, S3) Proven ability to move models from experimentation into live systems Experience with MLOps tools (MLflow, Weights & Biases, DVC, or similar) Hands-on exposure to LLM/GenAI ...

into commercial results. MLOps: Deep practical knowledge of MLOps principles and extensive experience with cloud-native ML services (e.g., Google Cloud Vertex AI, AWS SageMaker, Azure ML). Education: Ph.D. or Master's degree in Computer Science, Machine Learning, or a highly quantitative field, OR equivalent demonstrated technical leadership ...

looking for: Strong Python skills and experience with ML frameworks (scikit-learn, PyTorch, TensorFlow) Hands-on experience with cloud ML services (AWS SageMaker, Lambda, S3) Experience deploying ML/LLM models into production with MLOps best practices Strong experiment design, statistical evaluation, and problem-solving skills Excellent communication, able ...

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 ...

engineering, data quality validation, model training and optimisation. MLOps: experiment tracking (eg, MLflow), model registry, CI/CD for ML. Serving and orchestration: AWS SageMaker, EKS, batch & Real Time inference. Data pipelines: Spark/SQL, orchestration (Airflow), monitoring for drift/perf. Nice to Have Cost/performance optimisation ...

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 ...

with Django and Go) Demonstrated ability of productionising/deploying AI models Familiarity with the AWS cloud platform - AI/ML services such as SageMaker and Lambda University Degree in Computer Science, Engineering or Mathmatics If you are interested in the Data Scientist | UK's Fastest Growing AI Hospitality ...

constraints, monitoring and prompt versioning Strong Python skills and experience with PyTorch, TensorFlow or Keras Exposure to MLOps practices and hands-on experience with Sagemaker and/or Vertex AI Bachelor's degree in a technical field such as computer science or years of equivalent experience Comfortable working autonomously ...

learning concepts (classification, regression, clustering). Knowledge of big data platforms and cloud-based AI analytics environments (e.g., Databricks, Snowflake, Azure ML, or AWS SageMaker). Ability to present complex issues as simple, compelling, and data-driven narratives, enhanced by AI-supported visualization and summarization tools. Demonstrated curiosity ...

infrastructure, and cloud-native tooling. Tech Stack Programming: Python (Java familiarity is a plus). AWS: S3, Kinesis, Glue, Lambda, Step Functions, SageMaker, and more. On-Prem: Managed Kubernetes Platform and Hadoop ecosystem. Why This Role is Different Direct Impact: Build AI tools that traders and quants use daily ...

infrastructure, and cloud-native tooling. Tech Stack Programming: Python (Java familiarity is a plus). AWS: S3, Kinesis, Glue, Lambda, Step Functions, SageMaker, and more. On-Prem: Managed Kubernetes Platform and Hadoop ecosystem. Why This Role is Different Direct Impact: Build AI tools that traders and quants use daily ...

constrained environments Familiarity with representation learning or self-supervised approaches Research background or publications in relevant areas Tech stack • ML/AI: PyTorch, MLflow, SageMaker, ZenML • Infrastructure: AWS, Kubernetes, Docker • Edge deployment: CoreML, ONNX • Data: Python, S3, multimodal sensor data pipelines • Collaboration: JIRA, Git, structured OKR methodology ...

containerisation (Docker, Kubernetes) and orchestration of multi-stage ML workflows. Hands-on experience with ML platforms and tools such as MLflow, Kubeflow, Vertex AI, SageMaker, or similar model management systems. Practical knowledge of infrastructure as code, CI/CD best practices, and cloud platforms (AWS, GCP, or Azure). ...

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 ...

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 ...

Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million Users | UK Remote OR London, Hybrid, 1 Day PW, Up to £140,000 About the Company Our client is an extremely well know, digital marketplace focused on sustainable ...

focus on delivery. What you’ll be working on Setting up and improving MLflow for experiment tracking and model registry Building and supporting AWS SageMaker environments for model training and experimentation Developing ETL/data ingestion pipelines, using tools such as Dagster or Argo Putting in place standard MLOps … evaluation and monitoring frameworks Explainability tooling Essential Strong experience in MLOps/ML platform engineering Solid Python skills Hands-on experience with AWS, particularly SageMaker and S3 Experience with Docker and CI/CD pipelines Background building or maintaining ETL/orchestration workflows Experience using MLflow or a similar ...