76 to 80 of 80 Permanent Memory Management Jobs

architectural patterns such as MVC and MVVM. Experience working on applications that interface with connected devices or embedded systems (e.g. Bluetooth, IoT). A solid understanding of performance tuning, memory management, and UX principles on iOS. Strong communication and leadership skills, with the ability to drive collaboration across technical and non-technical teams. Offering a competitive salary, state More ❯

Work with the Studio Technical Director and the early team to set-up the project in UE5 Architect and implement foundational game systems (e.g., input, save/load, streaming, memory management, performance profiling, etc.) for a new AAA console title. Collaborate with technical leadership to define the game’s technical vision and ensure alignment with project goals. Establish … UE5 (including Gameplay Framework, Blueprints, and Engine subsystems). Proven experience in architecting game systems and leading technical direction on large-scale projects. Strong understanding of console development pipelines, memory/performance constraints, and platform-specific requirements. Excellent debugging, profiling, and optimization skills. Strong communication and leadership skills, with a collaborative mindset. Passion for delivering a world class player More ❯

years professional experience in native mobile development Experience implementing modern platform design patterns Understanding of testing iOS applications using platform tools Experience with production monitoring Basic proficiency with swift memory management Understanding of advanced swift features such as generics/concurrency mgmt/Experience with dependency management tools in iOS - SPM/Cocoapods/Carthage etc Basic More ❯

Rapidly build and iterate on LLM- and agent-based prototypes for various use cases, including chatbots, copilots, and A2A task agents. Implement agentic workflows, multi-step reasoning pipelines, and memory management using frameworks such as LangChain, CrewAI, and Autogen. Engineer and tune prompts to enhance the performance and reliability of generative tasks. Design RAG systems using vector databases … grounded LLM responses. Utilize Guardrails to implement applications that adhere to responsible AI guidelines. Optimize model performance for latency, throughput, and cost-efficiency. Implement short-term and long-term memory modules to support persistent agent behaviours. Use cloud platforms such as Amazon Bedrock, Google Vertex AI, and Azure AI Studio for model orchestration and deployment. Build and integrate UI More ❯

innovation-driven role focused on rapidly prototyping advanced AI systems using LLMs, autonomous agents, and semantic search. The engineer will work across the full stack-from prompt engineering and memory management to UI and cloud deployment-using tools like LangChain, CrewAI, and vector databases. Core Responsibilities Build and iterate on LLM/agent-based prototypes (e.g., copilots, chatbots … A2A agents). Implement multi-step reasoning, memory modules, and RAG pipelines. Use frameworks like LangChain, LangGraph, CrewAI, and tools like Pinecone, FAISS. Optimize performance and ensure responsible AI practices. Deploy via cloud platforms (AWS Bedrock, Azure AI, Google Vertex). Build UIs (Streamlit, Gradio, React) and integrate APIs and databases. Preferred Skills Experience with multi-agent systems and More ❯