Job Description
We are not just building software; we are engineering the future. At Nexus Horizon AI, we are preparing for the technological paradigm shift of 2026. We are seeking a visionary Senior AI Architect to lead our research into next-generation autonomous agents and scalable Generative AI architectures.
In this pivotal role, you will define the technical roadmap for our proprietary AI systems, ensuring they are robust, efficient, and scalable for enterprise deployment. You will bridge the gap between theoretical research and production-grade engineering, working with a world-class team of data scientists and engineers.
Why Join Us?
- Impactful Work: Build the foundational AI models that will power the next decade of technology.
- Future-Ready: Work on cutting-edge technologies including Quantum-ready algorithms and Edge AI optimization.
- Equity Package: Competitive compensation with significant equity stake in a Series B startup.
If you are passionate about the trajectory of AI and want to shape the landscape of 2026, we want to hear from you.
Responsibilities
- Architectural Leadership: Design and implement scalable, fault-tolerant AI infrastructure capable of handling millions of concurrent inference requests.
- Model Optimization: Lead efforts to optimize Large Language Models (LLMs) for latency, memory efficiency, and reduced token costs.
- Research Integration: Translate theoretical research papers into production-ready code and integrate novel algorithms into our core product stack.
- Technical Mentorship: Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
- Cross-Functional Collaboration: Partner with product managers and engineering teams to define technical requirements and delivery milestones.
- Security & Compliance: Implement rigorous security protocols and ensure all AI deployments comply with industry standards (SOC2, GDPR).
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Mathematics, Physics, or a related field.
- Experience: 5+ years of professional experience in Machine Learning Engineering, AI Architecture, or Applied Research.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, or JAX. Experience with Rust or Go is a strong plus.
- Modeling: Deep understanding of Deep Learning architectures, specifically Transformers, GANs, and diffusion models.
- Infrastructure: Experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).
- Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.