8 of 8 Remote Memory Management Jobs in Central London

of tick data , time-series databases , and real-time market data . Experience working with global market data feeds (e.g., Bloomberg, Reuters, FIX, Kafka). Proficiency in performance tuning, memory management, and multi-threaded programming in KDB+ . Comfortable working in Agile/DevOps environments, including CI/CD pipelines. Familiarity with Linux systems , scripting (Python/Bash More ❯

have the following: • Advanced proficiency in Java • Strong experience in low-latency, high-throughput systems, particularly within FX trading platforms (e.g. LSE, 360T) • Deep understanding of efficient garbage collection, memory management, and object modeling • Unit testing experience with Grabler, JUnit, or similar frameworks • Proficient in Oracle or similar relational databases • Comfortable working in agile environments, especially those transitioning More ❯

Kubernetes. Excellent interpersonal and communication abilities, enabling effective teamwork and collaboration. Strong knowledge of both Linux and Windows operating systems. Proven experience working with multi-threaded applications and complex memory management scenarios. Confident navigating across multiple technology domains and full software stacks. Passionate about learning and committed to continuous professional growth. Exposure to high-level languages; Python and More ❯

least 3 years of modern C++ experience in a commercial environment. Experience with C++17 and newer is a MUST. Solid understanding of OOP concepts and modern C++ features, including memory management facilities such as smart pointers, move semantics, etc. Experience with multi-threaded applications and TCP networking. The ability to produce good quality code in a timely manner. More ❯

real-time decision-making in autonomous driving. What to Expect The successful candidate will focus on host-side software and hardware interactions to ensure optimal data transfer and resource management for efficient AI inference on GPUs. Key responsibilities include Developing and optimizing C++ code for efficient data transfer and latency management between the host and GPUs across diverse … vendor platforms. Working with low-level system and memory management techniques to minimize latency and improve real-time inference performance. Utilizing and implementing GPU programming APIs (e.g., CUDA, OpenCL) to ensure high efficiency and compatibility across GPUs. Profiling and debugging system performance using tools like NVIDIA Nsight, Intel VTune, and vendor-specific profilers, identifying bottlenecks and implementing effective … modern C++ standards. Proven experience in GPU programming and optimization, with proficiency in CUDA, OpenCL, or other GPU programming frameworks. Strong knowledge of parallel computing concepts, including data locality, memory access patterns, and synchronization. Proficiency with performance profiling tools and techniques for identifying and resolving system bottlenecks. Experience in system-level programming, including memory management, data alignment More ❯

and LangFlow. Implement retrieval-augmented generation (RAG) pipelines using vector databases like Pinecone, FAISS, Chroma, or PostgreSQL. Fine-tune prompts to optimise performance, reliability, and alignment. Design and implement memory modules for short-term and long-term agent behaviours. Deploy models and orchestrate AI systems on cloud platforms such as AWS Bedrock, Google Vertex AI, and Azure AI Studio. … collaboratively with their teams, Google Premier Cloud Partner experience etc Proven track record designing and deploying agentic and generative AI prototypes. Deep understanding of semantic search, vector databases, and memory management strategies. Familiarity with cloud AI tools, observability platforms, and performance optimisation. This is an opportunity to work at the forefront of AI innovation, where your work will More ❯

and LangFlow. • Implement retrieval-augmented generation (RAG) pipelines using vector databases like Pinecone, FAISS, Chroma, or PostgreSQL. • Fine-tune prompts to optimise performance, reliability, and alignment. • Design and implement memory modules for short-term and long-term agent behaviours. • Deploy models and orchestrate AI systems on cloud platforms such as AWS Bedrock, Google Vertex AI, and Azure AI Studio. … collaboratively with their teams, Google Premier Cloud Partner experience etc • Proven track record designing and deploying agentic and generative AI prototypes. • Deep understanding of semantic search, vector databases, and memory management strategies. • Familiarity with cloud AI tools, observability platforms, and performance optimisation. This is an opportunity to work at the forefront of AI innovation, where your work will More ❯

and LangFlow. • Implement retrieval-augmented generation (RAG) pipelines using vector databases like Pinecone, FAISS, Chroma, or PostgreSQL. • Fine-tune prompts to optimise performance, reliability, and alignment. • Design and implement memory modules for short-term and long-term agent behaviours. • Deploy models and orchestrate AI systems on cloud platforms such as AWS Bedrock, Google Vertex AI, and Azure AI Studio. … collaboratively with their teams, Google Premier Cloud Partner experience etc • Proven track record designing and deploying agentic and generative AI prototypes. • Deep understanding of semantic search, vector databases, and memory management strategies. • Familiarity with cloud AI tools, observability platforms, and performance optimisation. This is an opportunity to work at the forefront of AI innovation, where your work will More ❯