Job Description
Are you ready to build the systems that will define the technological landscape of 2026? Nexus Horizon is a pioneering AI research firm dedicated to bridging the gap between today's algorithms and tomorrow's reality. We are seeking a visionary Lead AI Architect to lead our core engineering division, focusing on scalable, ethical, and high-performance machine learning systems.
In this role, you won't just maintain existing systems; you will architect the infrastructure that powers our next-generation predictive models and neural interfaces. We are looking for a thought leader who thrives in ambiguity and has a passion for pushing the boundaries of what is possible in artificial intelligence.
Why Join Nexus Horizon?
- Future-Ready Tech Stack: Work with the latest in Generative AI, Large Language Models, and edge computing.
- Impactful Work: Your code will directly influence how industries operate in the future.
- Competitive Compensation: Base salary plus performance-based equity.
- Remote-First Culture: Flexible working arrangements for top talent.
Responsibilities
- Design and implement robust, scalable AI architectures capable of handling petabyte-scale data.
- Lead the research and development of proprietary machine learning algorithms tailored for 2026 market needs.
- Collaborate with cross-functional teams (Data Science, Product, Security) to integrate AI solutions seamlessly.
- Establish best practices for code quality, testing, and deployment within the AI ecosystem.
- Provide technical mentorship to junior engineers and drive continuous learning within the engineering department.
- Evaluate emerging technologies (e.g., neuromorphic computing, quantum ML) to determine feasibility for implementation.
Qualifications
- Master’s degree or PhD in Computer Science, Mathematics, or a related technical field (or equivalent professional experience).
- Minimum of 8 years of professional experience in software engineering, with at least 4 years specifically in AI/ML architecture.
- Deep expertise in Python, TensorFlow, PyTorch, or similar ML frameworks.
- Strong understanding of distributed systems, cloud infrastructure (AWS/GCP/Azure), and containerization (Docker/Kubernetes).
- Proven track record of leading high-performance engineering teams and delivering complex projects on time.
- Excellent problem-solving skills with a focus on ethical AI and bias mitigation.