4 of 4 Remote AWS Lambda Jobs in Oxfordshire

In this role you will: Design, develop, test, and deploy high-quality, scalable, and maintainable third-party integrations Work extensively with RESTful APIs, webhooks, and other integration patterns. Leverage AWS services, with a strong focus on AWS Lambdas. Work with UI developers to develop and maintain user-facing features. Participate in code reviews to ensure code quality, share … environment. Proven experience in designing and building scalable, and maintainable applications using Java. ( Java 8+, with experience or a strong desire to work with Java 21). Familiarity with AWS, and core services (e.g., EC2, S3, AWS Lambda). Proven experience with the Spring Boot framework. Hands-on experience with building and consuming RESTful APIs. Experience with … both technical and non-technical stakeholders. Technical design and documentation skills. Attention to detail and a genuine interest in technological trends. Experience in the FinTech industry. Direct experience with AWS services like SQS, SNS, and API Gateway. Familiarity with containerisation technologies such as Docker. Experience with Infrastructure as Code (IaC) tools like AWS CloudFormation. Knowledge of Git and More ❯

a modern ML Ops stack, which includes data acquisition pipelines, data management systems, and ML model training infrastructure. This stack combines self-managed on-premises systems with cloud-based AWS resources. As an ML Ops Engineer, you'll have the opportunity to influence technical direction, propose new solutions, and potentially lead projects within the team. The company offers a … maintain on-premise Kubernetes clusters Implement and maintain ML Ops pipelines using Kubeflow and similar tools (e.g., MLflow) Develop scripts and tooling in Python; manage Linux system configurations Leverage AWS infrastructure (Cognito, S3, EC2, Lambda, etc.) Integrate ML toolkits (e.g., PyTorch, Lightning) into ML Ops workflows Design and deploy robust ML Ops solutions across various technologies Contribute to … Skills and Experience: Solid experience managing on-premise Kubernetes clusters Strong knowledge of Kubeflow or similar ML Ops platforms Proficiency in Python programming, Linux systems, and scripting Experience with AWS services (Cognito, S3, EC2, Lambda, etc.) Familiarity with ML frameworks such as PyTorch or Lightning, and understanding their role in ML Ops pipelines Ability to design and implement More ❯

a modern ML Ops stack, which includes data acquisition pipelines, data management systems, and ML model training infrastructure. This stack combines self-managed on-premises systems with cloud-based AWS resources. As an ML Ops Engineer, you’ll have the opportunity to influence technical direction, propose new solutions, and potentially lead projects within the team. The company offers a … maintain on-premise Kubernetes clusters Implement and maintain ML Ops pipelines using Kubeflow and similar tools (e.g., MLflow) Develop scripts and tooling in Python; manage Linux system configurations Leverage AWS infrastructure (Cognito, S3, EC2, Lambda, etc.) Integrate ML toolkits (e.g., PyTorch, Lightning) into ML Ops workflows Design and deploy robust ML Ops solutions across various technologies Contribute to … Skills and Experience: Solid experience managing on-premise Kubernetes clusters Strong knowledge of Kubeflow or similar ML Ops platforms Proficiency in Python programming, Linux systems, and scripting Experience with AWS services (Cognito, S3, EC2, Lambda, etc.) Familiarity with ML frameworks such as PyTorch or Lightning, and understanding their role in ML Ops pipelines Ability to design and implement More ❯

relevant field Strong experience managing on premise Kubernetes clusters Deep knowledge of Kubeflow or similar systems such as MLflow Proficient in Python and experienced with Linux systems Familiar with AWS services such as Cognito, S3, EC2 and Lambda Experience working with ML frameworks such as PyTorch or Lightning Capable of designing and delivering ML Ops solutions across various More ❯