Job Description
Are you ready to define the technological landscape of 2026? Synapse Future is a cutting-edge R&D firm pioneering the next generation of Artificial General Intelligence (AGI) and neural interfaces. We are seeking a visionary Senior AI Architect to lead our core infrastructure team.
In this role, you won't just be maintaining legacy systems; you will architect the foundational frameworks that will power autonomous decision-making, quantum-ready neural networks, and next-gen user experiences. If you thrive in ambiguity and are obsessed with pushing the boundaries of what's possible in machine learning, we want to meet you.
Responsibilities
- Architect Scalable Systems: Design and implement robust, distributed AI infrastructure capable of handling petabyte-scale data ingestion and real-time inference.
- Lead Research Integration: Bridge the gap between theoretical research and production-grade engineering by integrating cutting-edge transformer models and reinforcement learning algorithms.
- Optimize Neural Performance: Drive efficiency improvements in model training and inference latency, specifically focusing on edge-computing environments and quantum-ready architectures.
- Technical Mentorship: Cultivate a high-performance engineering culture by mentoring junior developers and data scientists on best practices in deep learning and software architecture.
- Strategic Roadmapping: Collaborate with C-level leadership to define the technical roadmap for our 2026 product releases and research initiatives.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field (PhD preferred).
- Experience: 7+ years of professional experience in software engineering and machine learning, with at least 3 years in a senior architect or lead role.
- Technical Stack: Deep expertise in Python, PyTorch, TensorFlow, and distributed computing frameworks (e.g., Kubernetes, Apache Spark).
- Specialization: Proven track record of working with Large Language Models (LLMs), Generative AI, or multi-modal AI systems.
- Problem Solving: Exceptional ability to solve complex, unstructured problems and design systems that are scalable, secure, and maintainable.