11 of 11 Remote Amazon SageMaker Jobs in London

Learning Engineer to join the growing data science and AI team. You'll play a key role in designing, developing, and deploying scalable machine learning solutions using Python and Amazon SageMaker . This role is based UK Wide. This role will be Via Umbrella. Working in a Hybrid Model of 1 day a week on site. Key Responsibilities … Design and implement machine learning models for classification, regression, and forecasting tasks. Build and manage end-to-end ML pipelines using Amazon SageMaker . Collaborate with data scientists, engineers, and product teams to integrate ML solutions into production systems. Optimise model performance and scalability. Monitor and maintain deployed models, ensuring reliability and accuracy. Stay up-to-date with … research and tools. Required Skills & Experience Strong proficiency in Python and its ML/data libraries (e.g., NumPy, pandas, scikit-learn, TensorFlow or PyTorch). Hands-on experience with Amazon SageMaker , including training, tuning, and deploying models. Solid understanding of machine learning algorithms and statistical methods. Experience with cloud platforms (AWS preferred). Familiarity with CI/CD More ❯

certification desirable). Proven experience deploying and supporting LLMs in production. Strong understanding of LLM fine-tuning (PyTorch, TensorFlow, Hugging Face Trainer, etc.). Experience with ML tooling (e.g. SageMaker, LangChain/LangSmith, MLflow, Dataiku, DataRobot). Knowledge of embeddings, their applications, and limitations. Hands-on experience in Agile/Lean/XP environments. Excellent communication, problem-solving, and More ❯

certification desirable). Proven experience deploying and supporting LLMs in production. Strong understanding of LLM fine-tuning (PyTorch, TensorFlow, Hugging Face Trainer, etc.). Experience with ML tooling (e.g. SageMaker, LangChain/LangSmith, MLflow, Dataiku, DataRobot). Knowledge of embeddings, their applications, and limitations. Hands-on experience in Agile/Lean/XP environments. Excellent communication, problem-solving, and More ❯

to support decisions across multiple business areas, including marketing, sales, claims, retention, customer behavior, fraud detection, and customer servicing. Deploy machine learning models into production using AWS services, including SageMaker, S3, Feature Store, ensuring scalable, reliable, and monitored solutions that directly support key business processes. Collaborate with product management and engineering teams to integrate data-driven insights and deploy More ❯

Terraform for infrastructure management Grafana, Elasticsearch, Kibana & New Relic for metrics, logs and monitoring In the company we also use: VueJS, MySQL, Spring Boot, Apache Camel, AWS Redshift, AWS SageMaker, Pentaho, Balena, Serverless functions Winnow has adopted a hybrid working model where employees come to the office two days a week and can choose to work from home or More ❯

at Lyst. We work mainly in Python using all the standard ML toolkits and frameworks (e.g. SKLearn, Tensorflow, Pytorch), and run our ML code in the AWS environment using Sagemaker where possible. We have a strong preference for clean, documented, well tested and reviewed code and have tooling and a culture to support this. This is a hands-on More ❯

Bonus Points For Prior consulting experience in a top-tier firm or internal transformation role within Financial Services Familiarity with AI tools or platforms such as Azure AI, AWS SageMaker, or TensorFlow Hands-on experience implementing AI use cases in regulated environments Knowledge of frameworks like NIST AI RMF, ISO 38507, or DAMA DMBOK Relevant certifications in Responsible AI More ❯

Lyst is a global fashion shopping platform founded in London in 2010 and catering to over 160M shoppers per year. We offer our customers the largest assortment of premium & luxury fashion products in one place, curating pieces from 27,000 More ❯

other language services Expert in Machine Learning, Modeling, and development with Python Expert in MLOps with at least one platform, e.g.: MLflow, Kubeflow, or end-to-end automation with SageMaker services Ability to mentor others and work independently Nice to Have Production experience with any of the following is a plus: GenAI, LLMs, Recommendation Engines, AWS offerings for AI … and ML including SageMaker, Bedrock, Lex Knowledge of relevant regulations in AI/ML and incorporating compliance into MLOps processes Bachelor's degree or higher in computer science, engineering, or information systems Veeva's headquarters is located in the San Francisco Bay Area with offices in more than 15 countries around the world. As an equal opportunity employer, Veeva More ❯

facing role blends data analyst and data engineer skills, including requirement gathering, stakeholder communication, and delivering robust data solutions. Hands-on experience with Power BI, Sisense, Quicksight, and AWS (Sagemaker Unified Studio preferred) is highly desirable. Offering a competitive salary, performance-based bonuses, and fully flexible remote working, this is a fantastic opportunity to shape and lead analytics projects … analysis, cleansing, enrichment, metadata management, and data innovation. Proficiency in SQL and MySQL. Experience with business intelligence tools: Power BI, Sisense, Quicksight. Hands-on experience with ETL tools, ideally Sagemaker Unified Studio. Ability to validate, test, and build data engineering solutions. Strong communication skills with ability to translate between technical and non-technical stakeholders. Desirable 2-5 years' client More ❯

facing role blends data analyst and data engineer skills, including requirement gathering, stakeholder communication, and delivering robust data solutions. Hands-on experience with Power BI, Sisense, Quicksight, and AWS (Sagemaker Unified Studio preferred) is highly desirable. Offering a competitive salary, performance-based bonuses, and fully flexible remote working, this is a fantastic opportunity to shape and lead analytics projects … analysis, cleansing, enrichment, metadata management, and data innovation. Proficiency in SQL and MySQL. Experience with business intelligence tools: Power BI, Sisense, Quicksight. Hands-on experience with ETL tools, ideally Sagemaker Unified Studio. Ability to validate, test, and build data engineering solutions. Strong communication skills with ability to translate between technical and non-technical stakeholders. Desirable 2-5 years' client More ❯