1 to 25 of 40 Amazon SageMaker Jobs in the North West

large language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data ...

large language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data ...

large language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data ...

large language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data ...

least one major cloud provider. AWS, GCP or Azure Familiar with Docker and CI/CD pipelines Experience with managed ML platforms such as SageMaker, Vertex AI or Azure ML Data engineering and MLOps Experience with data warehouses such as Snowflake, BigQuery or Redshift Workflow orchestration using tools like ...

least one major cloud provider. AWS, GCP or Azure Familiar with Docker and CI/CD pipelines Experience with managed ML platforms such as SageMaker, Vertex AI or Azure ML Data engineering and MLOps Experience with data warehouses such as Snowflake, BigQuery or Redshift Workflow orchestration using tools like ...

versioning. 4. MLOps & Automation Implement MLOps practices including CI/CD for ML, model versioning, and experiment tracking. Use tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML. Automate model training, testing, deployment, and monitoring workflows. 5. Cloud & Infrastructure Build ML solutions on cloud platforms such ...

versioning. 4. MLOps & Automation Implement MLOps practices including CI/CD for ML, model versioning, and experiment tracking. Use tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML. Automate model training, testing, deployment, and monitoring workflows. 5. Cloud & Infrastructure Build ML solutions on cloud platforms such ...

versioning. 4. MLOps & Automation Implement MLOps practices including CI/CD for ML, model versioning, and experiment tracking. Use tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML. Automate model training, testing, deployment, and monitoring workflows. 5. Cloud & Infrastructure Build ML solutions on cloud platforms such ...

management. Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

management. Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

management. Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

management. Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

management. Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Develop in one or more core technology areas: NoSQL (MongoDB, DocumentDB) Graph databases (GraphDB, Neo4j) Search technologies (ElasticSearch, OpenSearch, SOLR) ML/AI frameworks (SageMaker, Bedrock) Cloud-based data engineering (AWS) Build and maintain cloud-native data pipelines, ensuring data quality, accuracy, and reliability. What We're Looking ...