3 of 3 Memory Management Jobs in Edinburgh

handling, generics and the standard library Go concurrency patterns, including goroutines, channels and the context package React, including modern hooks‐based development and state management TypeScript for building robust, type‐safe frontends Go web frameworks and routers such as net/http, Gin, Echo or Chi Data access … functional layers, including Go's built‐in testing tooling and frontend testing frameworks such as Jest or React Testing Library Go modules and dependency management Go performance fundamentals, including profiling with pprof, memory management and garbage collection behaviou Technical Excellence & Craft Mastery Write clean, maintainable and highly ...

skills and application of various strategies Use of RTOSs such as VxWorks or embedded Linux Deployment of software to distributed hardware platforms, multicore programming, memory management techniques, device driver development, code optimisation, interrupt-driven designs A good understanding of electronics, schematic design and use of test equipment Experience … developing solutions for ARM and Intel based multicore processing platforms Communication protocols (I2C, SPI, USB, Serial, Network, PCIe) Familiarity with configuration management tools, defect tracking and peer review Working alongside firmware and hardware engineers to develop working embedded solutions Knowledge of standards such as DO-178C and coding standards ...

engineer to a space that often lacks it. Key Responsibilities Design and implement production agentic AI systems on Amazon Bedrock, including multi-agent orchestration, memory management, and tool integration using Amazon Bedrock AgentCore and Strands Agents Build, integrate, and maintain MCP (Model Context Protocol) servers that expose capabilities … tracing tooling — CloudWatch, spans, and traces — to support debugging, performance monitoring, and compliance requirements Integrate LLMs into client applications through prompt engineering, context management, and function/tool calling patterns Leverage serverless infrastructure — AWS Lambda, DynamoDB, S3 — to build scalable, cost-efficient backends for AI workloads Collaborate with client ...