Julia Architect at Symbolic Mind We’re looking for a hands-on Julia expert who can help us develope the core architecture behind our AI models. You’ll design how these models are trained, optimized, and deployed—focusing on speed, scalability, and real-world usability. This role combines system design, high-performance computing, and modern LLM development. If you enjoy solving hard technical problems, building clean systems, and pushing what Julia can do at scale, you’ll fit right in. What You’ll Do Architect and build core components for training and serving LLMs. Make Julia code fast—parallel, memory-efficient, hardware-aware. Design infrastructure for data pipelines, experiments, evaluation, and deployment. Optimize training and inference costs on CPUs/GPUs and distributed systems. Work closely with research and engineering teams to turn ideas into production. Ensure models can run securely in enterprise environments (on-prem, VPC, private data). Mentor engineers and help define technical direction. Be a team player. What You Bring Strong, practical experience with Julia, especially performance and systems work. Background in large-model training, distributed compute, or LLM architectures. Skills in Python/C/C++ for integration and low-level components. Solid understanding of algorithms, numerical computing, and software architecture. Experience building and shipping production quality ML or AI systems. Bonus Skills Experience with reinforcement learning, or hybrid neuro-symbolic approaches. MLOps/DevOps tools (Docker, Kubernetes, CI/CD). Cloud, on-prem, or HPC environments. Open-source contributions in Julia or ML. Background in physics. Why Join Real ownership and meaningful equity. A chance to shape the foundation of a next-generation AI platform. Flexible remote/hybrid work. A smart, supportive team focused on real impact—not hype. Multicultural and diverse environment which highly values knowledge and exchange of ideas, supportive and positive attitude in the team.