Applied Scientist

Overview We're Hiring Join Our Team Applied Scientist - AI Operating System (Agentic AI startup) — Sydney, NSW, Australia Location: Sydney, NSW, Australia | Employment Type: Full time | Location Type: On-site We're seeking an exceptional AI Operating System Applied Scientist to join our SuperAgent team, reporting directly to the co-founder/Chief Science and Technology Officer. Join us in shaping the future of autonomous AI agents by designing the operating systems that will power the next generation of intelligent software. You'll be joining a team that values scientific rigor and engineering excellence, with the chance to make significant contributions to an emerging field. About us: NinjaTech AI is a generative AI startup (B2C and B2B) with headquarters in Silicon Valley and offices in Sydney and Vancouver. Our Engineering team is mostly ex-AWS and our Product and UX team is ex-Google. Backed by Alexa Fund and Samsung Ventures, we're on track to raise Series A funding in 2025. Our flagship product, SuperNinja, is an advanced agentic AI platform with full OS capabilities, performing website creation, end-to-end coding, advanced data analysis, and more. This is a full-time onsite position, based at our Sydney office (great office space, free meals). Our team works in a fast-paced and collaborative work environment. We get a lot done when we ideate together and iterate quickly. Why join NinjaTech AI: This is a unique opportunity for a motivated Applied Scientist to help build the foundation of next-generation AI agent systems. Unlike more commonly available AI/ML roles focused on model development, this position focuses on the critical infrastructure that will enable autonomous agents to operate effectively at scale. What makes you a strong match for this Science position: Research publications in systems for AI, virtualization, file systems, or related areas Experience translating research concepts into production-ready implementations Contributions to open-source AI projects or research communities Knowledge of vector databases and embedding techniques Hands-on experience with AWS Firecracker or other microVM implementations Expertise in designing and implementing fast file systems Experience with cloud-native security architectures and compliance frameworks Background in audit logging systems and security monitoring for AI applications Knowledge of performance optimization for virtualized environments in cloud settings Experience with secure multi-tenancy in AI systems Key challenges you will work on: Just as traditional operating systems manage resources, schedule tasks, and provide interfaces for applications, our AI Operating System will serve as the foundation for autonomous AI agents. We're creating a system that enables: Virtual Context Management: Allowing AI agents to effectively utilize memory beyond their limited context windows Resource Orchestration: Intelligently managing computational resources, memory, and storage for AI agents Tool Integration: Providing standardized interfaces for agents to interact with external tools and APIs Agent Collaboration: Facilitating communication and coordination between specialized AI agents Persistent Memory: Enabling agents to maintain and manage long-term memory across sessions Secure Isolation: Implementing microVM-based isolation for secure and efficient agent execution High-Performance Storage: Leveraging optimized file systems for AI workloads and memory management Comprehensive Auditing: Maintaining transparent records of all agent actions and resource usage Experience & Qualifications: 1+ years of industry experience (can be before or after PhD) PhD in Computer Science, Artificial Intelligence, or related field Strong research background demonstrated through publications or patents Familiarity with LLMs and their limitations Proficiency in Python and at least one systems programming language (C++, Rust, Go) Knowledge of memory management techniques and optimization Familiarity with AI agent frameworks and architectures Knowledge of high-performance file systems and storage optimization techniques Understanding of cloud-based virtualization architectures and containerization Background in security principles including isolation and access controls Excellent problem-solving skills and ability to work on complex systems Day-to-day responsibilities: You will report directly to the Chief Science and Technology Officer/Co-founder and will have ownership in these areas: Advanced Memory Management Systems: Research and develop novel approaches for AI agent memory hierarchies that effectively utilize different storage tiers and context management techniques MicroVM Isolation Architectures: Investigate state-of-the-art approaches to secure agent execution using Firecracker and other microVM technologies, focusing on performance optimization and security guarantees High-Performance AI File Systems: Research and develop specialized file systems optimized for AI workloads, with particular focus on fast access patterns, efficient vector storage, and memory-mapped approaches Cloud-Native Virtualization: Explore novel architectures for deploying AI agents in cloud environments with optimal resource utilization and scaling capabilities Security and Auditing Frameworks: Develop comprehensive approaches to AI system governance, including transparent logging, monitoring, and compliance verification Multi-Agent Collaboration Protocols: Design and implement efficient communication mechanisms between isolated agent instances Resource Optimization Algorithms: Create adaptive systems that intelligently allocate computational resources based on agent workloads and priorities NinjaTech AI offers competitive salary and excellent benefits: Annual Health insurance subsidy Superannuation Paid Time Off (Vacation, Sick & Holidays) #J-18808-Ljbffr