Who we are At Hiverge, our mission is to build algorithmic superintelligence: an AI discovery engine that automatically writes algorithms for the most critical optimisation problems. Our founding team is composed of world-class researchers from Google DeepMind and University of Cambridge, having co-developed AlphaTensor, FunSearch, and Nobel-prize winning AlphaFold. At Hiverge, you will be working with the brightest minds in AI, algorithms, and mathematics. If you’re passionate about AI and eager to shape transformative technologies, we’d love to hear from you. About this role We are seeking a senior engineer with a strong background in performance analysis and optimization. As part of our core team, you will contribute to building advanced machine learning systems that improve software efficiency and reliability. In addition to performance analysis, you may also work on performance-sensitive domains such as LLM inference, and model training. You will Design and develop performance profiling tools to analyze large codebases. Conduct benchmarking, identify bottlenecks, and propose improvements across software, hardware, and system layers. Implement monitoring, observability, and testing frameworks focused on performance metrics. Collaborate with product, research and engineering teams to ensure performance insights translate into practical product improvements. Contribute to open-source projects or share performance learnings with the community when applicable. Stay up to date with the latest advancements in compilers, runtime systems, ML frameworks, and AI performance engineering. Qualifications 5 years of experience in software engineering with a focus on performance optimization. Strong programming skills in Python, C++, Rust or Go Experience with performance profiling and benchmarking tools (e.g., perf, gprof, flame graphs). Deep understanding of system-level concepts such as memory management, concurrency, and distributed systems. What sets you apart Background in compiler optimization, runtime systems, or JIT execution. Hands-on experience with GPU programming, CUDA, or other hardware accelerators. Familiarity with ML frameworks (PyTorch, TensorFlow) and performance optimization for training/inference Prior contributions to open-source performance tools or ML frameworks is a big plus. We offer competitive compensation, generous benefits packages, and offer a stimulating work environment, with the opportunity to contribute to the future of generative AI.