1 to 25 of 48 Amazon SageMaker Jobs

certifications on the training platform of your choice. As a Senior Solution architect, you'll be implementing and driving large-scale cloud implementations on Amazon AWS. Other duties include: Architecting and implementing cloud solutions for different applications, automating cloud operations and cloud deployments Assume responsibility for the architecture of … with application development teams on same Cloud technology, ideally AWS including PaaS services such as S3, Lambda, Step Functions, ECS, Docker, SNS, SQS, Kinesis, SageMaker etc. Understanding of distributed application design, patterns, and experience producing design diagrams and documenting standards Qualifications Security Clearance eligible. You musthavethe right to work more »

certifications on the training platform of your choice. As a Senior Solution architect, you'll be implementing and driving large-scale cloud implementations on Amazon AWS. Other duties include: Architecting and implementing cloud solutions for different applications, automating cloud operations and cloud deployments Assume responsibility for the architecture of … with application development teams on same Cloud technology, ideally AWS including PaaS services such as S3, Lambda, Step Functions, ECS, Docker, SNS, SQS, Kinesis, SageMaker etc. Understanding of distributed application design, patterns, and experience producing design diagrams and documenting standards Qualifications Security Clearance eligible. You musthavethe right to work more »

pipelines. This role is critical in ensuring the high performance and reliability of our AI-driven solutions. Responsibilities: Deploy LLMs using platforms like Huggingface, Sagemaker, or similar. Manage deployment on multiple GPUs, ensuring optimal performance. Implement scaling and load balancing to handle varying loads efficiently. Design and maintain data more »

certifications on the training platform of your choice. As a Senior Solution architect, you'll be implementing and driving large-scale cloud implementations on Amazon AWS. Other duties include: Architecting and implementing cloud solutions for different applications, automating cloud operations and cloud deployments Assume responsibility for the architecture of … with application development teams on same Cloud technology, ideally AWS including PaaS services such as S3, Lambda, Step Functions, ECS, Docker, SNS, SQS, Kinesis, SageMaker etc. Understanding of distributed application design, patterns, and experience producing design diagrams and documenting standards Qualifications Security Clearance eligible. You musthavethe right to work more »

certifications on the training platform of your choice. As a Senior Solution architect, you'll be implementing and driving large-scale cloud implementations on Amazon AWS. Other duties include: Architecting and implementing cloud solutions for different applications, automating cloud operations and cloud deployments Assume responsibility for the architecture of … with application development teams on same Cloud technology, ideally AWS including PaaS services such as S3, Lambda, Step Functions, ECS, Docker, SNS, SQS, Kinesis, SageMaker etc. Understanding of distributed application design, patterns, and experience producing design diagrams and documenting standards Qualifications Security Clearance eligible. You musthavethe right to work more »

with predictive analytics and AI, e.g. machine learning Working knowledge of data platforms such as Snowflake and Databricks; ML platforms such as Azure ML, Amazon SageMaker, Google Vertex, etc; as well as R and/or Python Familiarity with web technologies such as JavaScript, security protocols, application integration more »

certifications on the training platform of your choice. As a Senior Solution architect, you'll be implementing and driving large-scale cloud implementations on Amazon AWS. Other duties include: Architecting and implementing cloud solutions for different applications, automating cloud operations and cloud deployments Assume responsibility for the architecture of … with application development teams on same Cloud technology, ideally AWS including PaaS services such as S3, Lambda, Step Functions, ECS, Docker, SNS, SQS, Kinesis, SageMaker etc. Understanding of distributed application design, patterns, and experience producing design diagrams and documenting standards Qualifications Security Clearance eligible. You musthavethe right to work more »

At Amazon, we're working to be the most customer-centric company on earth. One customer experience that were constantly taking to new levels is how we fulfill and deliver customers orders. Our goal is to delight our customers by delivering their packages quickly and accurately, anywhere in the … world. To meet this goal, Amazon is continually striving to innovate and provide best-in-class service levels by pioneering new products and services in the last mile delivery space. Come join the team and help us work hard, have fun, and make history! The EU DSP Management team … new, step-change initiatives for the organization. Onboarding data to our data warehouse by building automated data pipelines utilizing eg Python in Lambda or Sagemaker to invoke API calls. Using statistical techniques and tools for strategic deep dives; generating actionable insights and effectively communicating recommendations to senior leadership. Inventing more »

months Contract, Inside IR35 Delivery of AWS-based data & analytics capabilities, built on foundational services such as EMR, Glue, MWAA, Dynamo, Kinesis, Kafka and Sagemaker AWS Cloud Data Platforms Architecture and AWS Cloud Security & Infrastructure Insurance or Regulated Financial Services Industries Solutioning within a modern data architecture context such more »

leading a data science team and managing complex projects. Expertise in machine learning, statistics, data management, and relevant technologies (e.g., Python, R, SQL, AWS SageMaker, Apache Airflow, Dbt, AWS Kinesis). Strong communication skills with the ability to explain complex data concepts to a non-technical audience. Knowledge of more »

other prompt engineering approaches, common AI/ML frameworks (e.g., TensorFlow, PyTorch), GIT, Docker and vector databases Demonstrated knowledge of cloud AI services (AWS SageMaker, GCP AI Platform, Azure ML) and APIs Proficiency in using and configuring Linux systems A demonstrated proficiency in containerization technologies such as docker Additional more »

other prompt engineering approaches, common AI/ML frameworks (e.g., TensorFlow, PyTorch), GIT, Docker and vector databases Demonstrated knowledge of cloud AI services (AWS SageMaker, GCP AI Platform, Azure ML) and APIs Proficiency in using and configuring Linux systems A demonstrated proficiency in containerization technologies such as docker Additional more »

other prompt engineering approaches, common AI/ML frameworks (e.g., TensorFlow, PyTorch), GIT, Docker and vector databases Demonstrated knowledge of cloud AI services (AWS SageMaker, GCP AI Platform, Azure ML) and APIs Proficiency in using and configuring Linux systems A demonstrated proficiency in containerization technologies such as docker Additional more »

other prompt engineering approaches, common AI/ML frameworks (e.g., TensorFlow, PyTorch), GIT, Docker and vector databases Demonstrated knowledge of cloud AI services (AWS SageMaker, GCP AI Platform, Azure ML) and APIs Proficiency in using and configuring Linux systems A demonstrated proficiency in containerization technologies such as docker Additional more »

other prompt engineering approaches, common AI/ML frameworks (e.g., TensorFlow, PyTorch), GIT, Docker and vector databases Demonstrated knowledge of cloud AI services (AWS SageMaker, GCP AI Platform, Azure ML) and APIs Proficiency in using and configuring Linux systems A demonstrated proficiency in containerization technologies such as docker Additional more »

other prompt engineering approaches, common AI/ML frameworks (e.g., TensorFlow, PyTorch), GIT, Docker and vector databases Demonstrated knowledge of cloud AI services (AWS SageMaker, GCP AI Platform, Azure ML) and APIs Proficiency in using and configuring Linux systems A demonstrated proficiency in containerization technologies such as docker Additional more »

other prompt engineering approaches, common AI/ML frameworks (e.g., TensorFlow, PyTorch), GIT, Docker and vector databases Demonstrated knowledge of cloud AI services (AWS SageMaker, GCP AI Platform, Azure ML) and APIs Proficiency in using and configuring Linux systems A demonstrated proficiency in containerization technologies such as docker Additional more »

other prompt engineering approaches, common AI/ML frameworks (e.g., TensorFlow, PyTorch), GIT, Docker and vector databases Demonstrated knowledge of cloud AI services (AWS SageMaker, GCP AI Platform, Azure ML) and APIs Proficiency in using and configuring Linux systems A demonstrated proficiency in containerization technologies such as docker Additional more »

other prompt engineering approaches, common AI/ML frameworks (e.g., TensorFlow, PyTorch), GIT, Docker and vector databases Demonstrated knowledge of cloud AI services (AWS SageMaker, GCP AI Platform, Azure ML) and APIs Proficiency in using and configuring Linux systems A demonstrated proficiency in containerization technologies such as docker Additional more »

engineering practices sch as CI/CD. Experience deploying/monitoring machine learning models and following best practices. The Ability to develop pipelines using SageMaker, MLFlow or similar frameworks. Strong experience with data programming frameworks such as Apache Spark. Understanding of common Data Science and Machine Learning models, libraries more »

Engineering Manager Type : Permanent Location : London Onsite Requirements : Hybrid - 2/3 days a week Salary : Ranging between £110,000 - £150,000 A leading global SaaS business at the forefront of cutting-edge technology are seeking a talented Engineer Manager more »

Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and deployment. Data Analytics and Big Data Technologies: Proficient in big data technologies such as Hadoop, Spark more »

Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and deployment. Data Analytics and Big Data Technologies: Proficient in big data technologies such as Hadoop, Spark more »

Good grasp of architecture and how best to integrate machine learning into backend services. Some experience with MLOps processes and tools. Experience with AWS SageMaker would be ideal. Understanding of CI/CD & DevOps principles. Experience working with cloud environments. If you feel you meet most, but not all more »

Previous role as an MLOps engineer Use of ML frameworks e.g. pytorch, tensorflow Familiarity with MLOps platforms e.g. Kubeflow, MLFlow, Tensorflow Extended, ClearML, VertexAI, Amazon SageMaker Experience deploying ML models in production environments Benefits We provide: Competitive salary, benchmarked against the market and reviewed annually Hybrid and/ more »