1 to 25 of 466 Remote Amazon SageMaker Jobs

teams to understand business objectives, identify data requirements, and define analytics goals. Develop and implement data analysis strategies using AWS analytics services, such as Amazon Redshift, Amazon Athena, Amazon EMR, and Amazon QuickSight. Design and build robust data pipelines and ETL processes to extract, transform, and … techniques to perform predictive and prescriptive analyses, clustering, segmentation, and pattern recognition. Identify key metrics, develop meaningful KPIs, and build dashboards and visualisations using Amazon QuickSight to enable data-driven decision-making. Conduct exploratory data analysis to uncover trends, patterns, and insights that inform product enhancements, user behaviour, and … 2.Proven experience as a Data Scientist, preferably in a cloud-based environment using AWS analytics services. 3.Strong proficiency in AWS analytics services, such as Amazon Redshift, Amazon Athena, Amazon EMR, and Amazon QuickSight. 4.Solid understanding of data modelling, ETL processes, and data warehousing concepts. 5.Proficiency in More ❯

integration challenges. You will help design and deliver high-quality, scalable features, including AI-enhanced flows, predictive monitoring tools, and automation capabilities powered by Amazon Bedrock, Amazon SageMaker, and other modern AI/ML frameworks. You’ll work cross-functionally to translate product vision into technical outcomes … problems, and expectations related to Integration Platforms. Collaborate on the design and integration of AI/ML models into platform features, leveraging tools like Amazon Bedrock, SageMaker, and other AWS native services. Investigate and prototype the use of natural language processing, anomaly detection, and intelligent automation in the … a willingness to collaborate effectively within a team. A keen focus on improving user experience Nice to have: Experience with Integration Platforms. Familiarity with Amazon SageMaker, Amazon Bedrock, or similar ML/AI platforms (or willingness to learn quickly) Exposure to LLMs, vector databases, or embedding techniques More ❯

integration challenges. You will help design and deliver high-quality, scalable features, including AI-enhanced flows, predictive monitoring tools, and automation capabilities powered by Amazon Bedrock, Amazon SageMaker, and other modern AI/ML frameworks. You’ll work cross-functionally to translate product vision into technical outcomes … sophisticated server-side and client-side features. Collaborate on the design and integration of AI/ML models into platform features, leveraging tools like Amazon Bedrock, SageMaker, and other AWS native services. Investigate and prototype the use of natural language processing, anomaly detection, and intelligent automation in the … a willingness to collaborate effectively within a team. A keen focus on improving user experience Nice to have: Experience with Integration Platforms. Familiarity with Amazon SageMaker, Amazon Bedrock, or similar ML/AI platforms (or willingness to learn quickly) Exposure to LLMs, vector databases, or embedding techniques More ❯

integration challenges. You will help design and deliver high-quality, scalable features, including AI-enhanced flows, predictive monitoring tools, and automation capabilities powered by Amazon Bedrock, Amazon SageMaker, and other modern AI/ML frameworks. You’ll work cross-functionally to translate product vision into technical outcomes … sophisticated server-side and client-side features. Collaborate on the design and integration of AI/ML models into platform features, leveraging tools like Amazon Bedrock, SageMaker, and other AWS native services. Investigate and prototype the use of natural language processing, anomaly detection, and intelligent automation in the … a willingness to collaborate effectively within a team. A keen focus on improving user experience Nice to have: Experience with Integration Platforms. Familiarity with Amazon SageMaker, Amazon Bedrock, or similar ML/AI platforms (or willingness to learn quickly) Exposure to LLMs, vector databases, or embedding techniques More ❯

integration challenges. You will help design and deliver high-quality, scalable features, including AI-enhanced flows, predictive monitoring tools, and automation capabilities powered by Amazon Bedrock, Amazon SageMaker, and other modern AI/ML frameworks. You’ll work cross-functionally to translate product vision into technical outcomes … sophisticated server-side and client-side features. Collaborate on the design and integration of AI/ML models into platform features, leveraging tools like Amazon Bedrock, SageMaker, and other AWS native services. Investigate and prototype the use of natural language processing, anomaly detection, and intelligent automation in the … a willingness to collaborate effectively within a team. A keen focus on improving user experience Nice to have: Experience with Integration Platforms. Familiarity with Amazon SageMaker, Amazon Bedrock, or similar ML/AI platforms (or willingness to learn quickly) Exposure to LLMs, vector databases, or embedding techniques More ❯

Specialty Proven track record of architecting, deploying, and optimizing complex cloud solutions for AI-driven workloads. Generative AI and Cutting-Edge Technologies: Expertise in Amazon Bedrock for deploying foundation models and managing scalable GenAI workloads. Proficiency in fine-tuning and deploying Large Language Models (LLMs) and multimodal AI using … Amazon SageMaker JumpStart and Hugging Face on AWS. Experience leveraging Amazon Q (formerly AWS CodeWhisperer) Business and Developer for AI-powered coding productivity and automation. Machine Learning Frameworks and Pipelines: In-depth knowledge of Amazon SageMaker, including Pipelines, Model Monitor, Data Wrangler, and SageMaker … model training with multi-GPU clusters and optimization for high-performance inference. Data Engineering and AI Workflow Optimization: Proficient in building data pipelines with Amazon S3, AWS Glue, Lake Formation, and Redshift for AI and ML workloads. Experienced in optimizing data preparation for large-scale AI model training and More ❯

Specialty Proven track record of architecting, deploying, and optimizing complex cloud solutions for AI-driven workloads. Generative AI and Cutting-Edge Technologies: Expertise in Amazon Bedrock for deploying foundation models and managing scalable GenAI workloads. Proficiency in fine-tuning and deploying Large Language Models (LLMs) and multimodal AI using … Amazon SageMaker JumpStart and Hugging Face on AWS. Experience leveraging Amazon Q (formerly AWS CodeWhisperer) Business and Developer for AI-powered coding productivity and automation. Machine Learning Frameworks and Pipelines: In-depth knowledge of Amazon SageMaker, including Pipelines, Model Monitor, Data Wrangler, and SageMaker … model training with multi-GPU clusters and optimization for high-performance inference. Data Engineering and AI Workflow Optimization: Proficient in building data pipelines with Amazon S3, AWS Glue, Lake Formation, and Redshift for AI and ML workloads. Experienced in optimizing data preparation for large-scale AI model training and More ❯

AWS Architect (SageMaker) Fraud Detection Startup (UK Remote) Location: UK (Remote) Salary: £70,000 £75,000 + Equity Job Type: Full-time, Permanent About Us My client is fraud detection/manipulation startup on a mission to protect businesses and consumers from digital fraud in real-time. Using cutting … and prevents fraudulent activity before it happens. As we grow our technical team, were looking for an experienced AWS Architect with strong expertise in Amazon SageMaker to lead the development of our cloud-based ML infrastructure. The Role As our AWS Architect, youll play a key role in … to support advanced machine learning models and real-time fraud detection capabilities. Your Responsibilities: Architect and implement scalable AWS solutions with a focus on SageMaker for training, deploying, and managing ML models. Work closely with data scientists and engineers to deliver reliable, production-grade ML workflows. Ensure best practices More ❯

Europe North Are you passionate about helping customers build solutions leveraging state-of-the-art Artificial Intelligence, Machine Learning and Deep Learning tools on Amazon Web Service (AWS)? Would you like to focus on developing agentic AI systems for our Europe North customers? Come join us! At Amazon … our other Subject Matter Experts (SMEs) in helping customers in Europe North (BeNeLux, Nordics and Baltics) design solutions that leverage our GenAI services, including Amazon Bedrock, Amazon SageMaker, and Amazon Q. As part of the team, you will work closely with customers to enable large-scale … customers about the art of the possible, while challenging the impossible, come build the future with us. A day in the life Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates More ❯

data science and MLOps/LLMOps workflows. Collaborate with Data Scientists to deploy, serve, and monitor LLMs in real-time and batch environments using Amazon SageMaker , Bedrock Implement Infrastructure-as-Code with AWS CDK , CloudFormation to provision and manage cloud environments. Build and maintain CI/CD pipelines … strong focus on building and delivering scalable infrastructure for ML and AI applications using Python and cloud native technologies Experience with cloud services, especially Amazon Web Services (AWS) - SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS. Proficiency in Infrastructure-as-Code using AWS CDK or CloudFormation … . Experience implementing and scaling MLOps workflows with tools such as MLflow, SageMaker Pipelines . Proven experience building, containerising, and deploying using Docker and Kubernetes . Hands-on experience with CI/CD tools ( GitHub Actions , CodePipeline , Jenkins ) and version control using Git/GitHub . Strong understanding of More ❯

Learning services +2 years of experience supporting the entire MLDLC, including post-deployment operations such as monitoring and maintenance +2 years of experience with Amazon Web Services (AWS) and/or Google Cloud Platform (GCP) Experience with at least 80%: PyTorch, Tensorflow, LangChain, scikit-learn, Redis, Elasticsearch, Amazon SageMaker, Google Vertex AI, Weights & Biases, FastAPI, Prometheus, Grafana, Apache Kafka, Apache Airflow, MLflow, KubeFlow Ability to break large, complex problems into well-defined steps, ensuring iterative development and continuous improvement Experience in cloud-native delivery, with a deep practical understanding of containerization technologies such as Kubernetes and More ❯

on cloud platforms, and experience in building end-to-end scalable ML infrastructure with on-premise DGX or cloud platforms including AWS EKS/SageMaker, Azure Machine Learning/AKS, or common ML platforms (ClearML, MLflow, Weights and Biases). Cloud & Automation: Strong understanding of AWS, Azure, containerization/ More ❯

public sector clients, including participating in RFI/RFP processes, preparing bids, and delivering presentations. Familiarity with data science platforms (e.g., Databricks, Dataiku, AzureML, SageMaker) and frameworks (e.g., Keras, TensorFlow, PyTorch, scikit-learn). Experience deploying solutions on Cloud platforms (AWS, Azure, Google Cloud) using provisioning tools like Terraform. More ❯

and pattern detection. Strong communication skills for presenting work to clients and managing stakeholder relationships. Experience with data science platforms (e.g., Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g., Keras, TensorFlow, PyTorch, scikit-learn). Experience deploying solutions on Cloud platforms (AWS, Azure, Google Cloud) including provisioning tools More ❯

work with private/public sector clients through RFI/RFP processes, bids, and presentations. Familiarity with data science platforms (e.g., Databricks, Dataiku, AzureML, SageMaker) and frameworks (e.g., Keras, TensorFlow, PyTorch, scikit-learn). Cloud experience in deploying solutions on AWS, Azure, or Google Cloud, including provisioning tools like More ❯

winning work with private/public sector clients through RFI/RFP, bids, and presentations. Familiarity with data science platforms (e.g., Databricks, Dataiku, AzureML, SageMaker) and frameworks (e.g., Keras, TensorFlow, PyTorch, scikit-learn). Cloud experience with AWS, Azure, Google Cloud, including provisioning tools like Terraform. Deployment experience using More ❯

work with private/public sector clients, including RFI/RFP processes, bids, and presentations. Familiarity with data science platforms (e.g., Databricks, Dataiku, AzureML, SageMaker) and frameworks (e.g., Keras, TensorFlow, PyTorch, scikit-learn). Experience deploying solutions to Cloud platforms (AWS, Azure, Google Cloud) and using Cloud provisioning tools 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, Azure 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, Azure 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, Azure 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, Azure 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, Azure 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, Azure 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, Azure More ❯

RFI/RFP processes, as a preferred bidder, documented bids, and face-to-face presentations. Experience with 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 ❯