1 to 25 of 46 Remote Amazon SageMaker Jobs in England

SQL, Unix-based systems, git, and github for collaboration and review). Machine/Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases). An understanding of Language Models, using and training/fine-tuning and a familiarity More ❯

Hands-on experience with AI/ML frameworks (Scikit-Learn, TensorFlow, Hugging Face, PyTorch). Familiarity with ML/Gen AI tools (LangChain, MLFlow, SageMaker, Bedrock, Weights & Biases). Experience with OAuth, JWT authentication mechanisms . Why Apply? Work on a cutting-edge AI/ML project with real More ❯

e.g., Airflow). Leverage expertise in cloud computing platforms (AWS and Azure) to build and optimize AI infrastructure, using services like AWS Bedrock, S3, SageMaker, Azure AI Search, etc. Champion ML governance by ensuring guidelines are followed, monitoring SLAs, and continuously improving the performance and reliability of AI solutions. More ❯

machines, and neural networks (deep learning experience strongly preferred) Knowledge of popular Cloud computing vendor (AWS and Azure) infrastructure & services e.g., AWS Bedrock, S3, SageMaker; Azure AI Search, OpenAI, blob storage, etc. Bachelor's degree (master's or higher strongly preferred) in machine learning, computer science, data science, applied More ❯

training and model optimization . Experience deploying ML models and LLMs in cloud environments and local environments. Proficiency with AWS infrastructure, including EC2, S3, SageMaker and Bedrock. Ability to build effective ML pipelines for research and development. Experience with ML model lifecycle tools (e.g., MLflow, DVC, Weights & Biases). More ❯

deep learning, computer vision, natural language processing, etc Experience in building ML models in production using AWS ecosystem, especially ML related services such as SageMaker Ability to work independently and collaboratively with multi-functional teams with excellent communication and presentation skill Experience in writing unit tests and documentation for More ❯

machines, and neural networks (deep learning experience strongly preferred) Knowledge of popular Cloud computing vendor (AWS and Azure) infrastructure & services e.g., AWS Bedrock, S3, SageMaker; Azure AI Search, OpenAI, blob storage, etc. Bachelor’s degree (master’s or higher strongly preferred) in machine learning, computer science, data science, applied More ❯

and deploying cloud-based data solutions on AWS, Azure, or Google Cloud. Proficiency in AI/ML ecosystems such as Azure ML, Databricks, MLflow, Amazon Sagemaker and/or Bedrock with experience deploying and monitoring models in production. Understanding of data governance, security, and compliance frameworks, including GDPR More ❯

and deploying cloud-based data solutions on AWS, Azure, or Google Cloud. Proficiency in AI/ML ecosystems such as Azure ML, Databricks, MLflow, Amazon Sagemaker and/or Bedrock with experience deploying and monitoring models in production. Understanding of data governance, security, and compliance frameworks, including GDPR More ❯

can avoid asking you about something you don’t know about as we get to know each other. AWS services : EC2, Lambda, API Gateway, SageMaker, S3 (or equivalent from Azure, Google Cloud) Programming languages : Python, C++ Deep Learning Frameworks : PyTorch, TensorFlow, CUDA DevOps and automation, testing : Terraform, Ansible, Pytest More ❯

and visualisation languages and libraries (SQL, Python and/or R, matplotlib/ggplot etc.) as well as supporting tools and platforms (e.g. git, Sagemaker, VS Code). A strong understanding of statistical concepts (hypothesis testing, sampling, probability distributions). Excellent communication and collaboration skills to effectively bridge the More ❯

the RFI/RFP process, as preferred bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn). Cloud platforms - demonstrable experience of building and deploying solutions to Cloud (e.g. AWS More ❯

enterprise systems and cloud platforms. Develop and optimize RESTful and GraphQL APIs to facilitate AI-driven interactions. Utilize AWS services (Lambda, S3, API Gateway, SageMaker, DynamoDB, ECS, etc.) to deploy scalable AI solutions. Implement Full Stack JavaScript (Node.js, React.js, Express, TypeScript, Next.js, etc.) applications to support AI-driven interfaces. More ❯

with data visualization platforms such as PowerBI, Tableau or Sigma Knowledge of any of the following tools is a plus: Databricks, Snowflake, Dataiku, AWS, Sagemaker Oil and gas industry experience is a plus We are actively seeking candidates for full-time, remote work within the US and UK. Atlanta More ❯

writing, visualisations, or presentations. Strong organisational skills with experience balancing multiple projects. Familiarity with Posit Connect, workflow orchestration tools (e.g., Airflow), AWS services (e.g., SageMaker, Redshift), or distributed computing tools (e.g., Spark, Kafka). Experience in a media or newsroom environment. Agile team experience. Advanced degree in Maths, Statistics More ❯

business in their Data Science, AI, and ML initiatives. Our Data & Analytics technology stack consists primarily of: Oracle tools, Snowflake, Postgres, various AWS Services (SageMaker, Lambda, Step Functions, DMS, S3 etc.) in the AWS Cloud. We are currently engaged on multiple data focused projects which are in various stages More ❯

down complex challenges, devise practical solutions, and iterate quickly based on feedback or data. Hands-on experience with cloud platforms, including AWS (e.g., EC2, Sagemaker, Bedrock, S3, Lambda), Google Cloud (e.g., Compute Engine, Vertex, GKE, BigQuery), Azure (e.g., Virtual Machines, Azure OpenAI) etc. Proficiency in scripting or programming (e.g. More ❯

in enterprise technology professional services, in a consulting or other customer-facing delivery role. AI-specific tools such as TensorFlow, Google Cloud AI Platform, Amazon SageMaker, etc. Working in a number of distinct industries/verticals. Success measures Within 3 months: Complete internal training on MongoDB. Be connected More ❯

experience in deploying ML and AI solutions in production on cloud and working with cross-functional teams to achieve that. Experience in AzureML or SageMaker will be highly valued. You have strong communication skills and proven experience in presenting work to clients and managing stakeholders. What does ‘Get The More ❯

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. LLM Deployment: Experience with local (cloud) deployment of OpenSource LLM, like LLAMA, DeepSeek. Bonus Points: Experience with Airbyte and More ❯

of security best practices in cloud-based applications Strong troubleshooting and problem-solving skills Nice to Have: Experience with Angular Framework Familiarity with AWS SageMaker or Bedrock Knowledge of Google Workspace and Atlassian tools (Jira, Confluence) Seniority level Entry level Employment type Full-time Job function Information Technology Industries More ❯

experience with Gen AI application monitoring tools such as Arize Pheonix and LangSmith. Hands-on experience with cloud AI platforms (Google Vertex AI, AWS SageMaker, Azure AI). Knowledge of GenAIOps, AI security, and responsible AI best practices . Ability to lead AI initiatives, mentor teams, and drive innovation More ❯

. Experience working on biological data curation, including data cleansing and preprocessing of -omics datasets. Exposure to cloud-based ML orchestration frameworks such as Sagemaker and Vertex AI. Experience with model deployment in an enterprise setting. For immediate consideration please send your most up to date CV to jason More ❯

models from OAS using oapi-codegen Launch Darkly Feature Flagging Docker AWS Cloud Services including EKS and RDS AWS Bedrock Knowledgebases and Agents AWS Sagemaker Generative AI Prompt Engineering Additional Information About QAD: QAD Inc. is a leading provider of adaptive, cloud-based enterprise software and services for global More ❯

Segment Commercial Tooling: Hubspot, Planhat, Intercom Company & Customer Analytics: Looker AI Tools & Frameworks: (to be built upon) TensorFlow/PyTorch for model development. AWS SageMaker or Vertex AI for scalable model deployment. OpenAI APIs or Hugging Face for generative AI applications. What are the benefits? People are our core More ❯