Job Description
We are building the infrastructure for the year 2026. Nexus Horizon Labs is seeking a visionary Advanced AI Architect to lead the development of next-generation generative models and autonomous systems. If you are passionate about pushing the boundaries of what is possible in Artificial General Intelligence (AGI) and want to define the technological landscape of the future, this is your opportunity to make a profound impact.
In this role, you will bridge the gap between theoretical research and scalable production engineering, ensuring our AI systems are not only intelligent but also ethical, secure, and efficient. Join a team of elite engineers and researchers dedicated to solving humanity's most complex challenges through advanced technology.
Responsibilities
- Architectural Leadership: Design and oversee the implementation of cutting-edge neural network architectures tailored for high-volume, low-latency deployment in 2026.
- R&D Strategy: Identify emerging AI paradigms, such as Quantum-Enhanced Machine Learning, and integrate them into our core product roadmap.
- System Optimization: Spearhead initiatives to improve model efficiency, reduce inference costs, and enhance data privacy compliance.
- Team Mentorship: Lead a team of senior ML engineers and data scientists, fostering a culture of innovation and technical excellence.
- Stakeholder Collaboration: Translate complex technical concepts into actionable insights for executive leadership and product teams.
- Future-Proofing: Proactively anticipate regulatory changes and technological shifts to ensure our infrastructure remains robust for the coming decade.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 7+ years of experience in machine learning engineering, with at least 2 years in a senior architectural or lead role.
- Technical Stack: Deep expertise in PyTorch, TensorFlow, or JAX; experience with distributed computing systems (Kubernetes, Ray) and cloud platforms (AWS/GCP).
- Domain Knowledge: Proven track record in developing LLMs, reinforcement learning agents, or multimodal systems.
- Problem Solving: Exceptional ability to troubleshoot complex system failures and optimize performance bottlenecks.
- Communication: Outstanding written and verbal communication skills with the ability to present technical strategies to non-technical audiences.