Job Description
Are you ready to shape the technological landscape of tomorrow?
Nexus 2026 is pioneering the next generation of autonomous systems and generative AI infrastructure. As we prepare to deploy our flagship solutions by the year 2026, we are seeking a visionary Lead AI Architect to define the core neural network architecture and scalability roadmap. You will be responsible for bridging the gap between theoretical AI models and high-performance, production-ready engineering systems.
In this role, you will lead a world-class team of engineers, define technical strategies for our upcoming roadmap, and ensure our systems are robust enough to handle the demands of the future.
Responsibilities
- Architect Design: Design and implement scalable, fault-tolerant AI systems and machine learning pipelines tailored for high-volume data processing.
- Roadmap Strategy: Lead the technical vision for Project 2026, defining milestones, architectural standards, and technology stacks for the 2026 release cycle.
- Team Leadership: Mentor senior engineers and data scientists, fostering a culture of innovation, code excellence, and continuous learning.
- Performance Optimization: Optimize model inference speeds and reduce latency to ensure real-time decision-making capabilities in mission-critical environments.
- Cross-Functional Collaboration: Work closely with product managers, researchers, and stakeholders to translate business requirements into technical blueprints.
- Security & Compliance: Implement rigorous security protocols and ensure all AI models comply with industry standards and ethical guidelines.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related field (PhD preferred).
- Experience: 10+ years of experience in software engineering, with at least 5 years in a lead or architect role within the AI/ML domain.
- Technical Stack: Deep proficiency in Python, PyTorch, TensorFlow, or JAX. Experience with distributed computing systems (Kubernetes, Docker) is required.
- Problem Solving: Proven track record of deploying complex machine learning models to production environments with high availability.
- Soft Skills: Exceptional communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.
- Future-Forward Mindset: Passionate about emerging technologies and the potential of AI to solve global challenges by 2026.