Job Description
Are you ready to define the technology landscape of 2026? Nexus Horizon Labs is pioneering the next generation of artificial intelligence, and we are seeking a visionary Lead AI Architect to join our elite R&D division.
In this role, you will bridge the gap between theoretical machine learning and scalable, real-world deployment. You will be instrumental in architecting systems that will power our platform through the next decade. If you are passionate about pushing the boundaries of what is possible in Generative AI, Neural Networks, and Quantum Computing integration, we want to hear from you.
Why join us?
- Work on mission-critical projects with a world-class team.
- Competitive equity package and comprehensive benefits.
- Flexible remote-first culture with state-of-the-art office amenities.
Key Objectives:
- Lead the architectural design for our 2026 AI roadmap.
- Optimize deep learning models for high-throughput environments.
- Collaborate with cross-functional teams to integrate AI solutions into core products.
Responsibilities
- System Architecture: Design scalable, fault-tolerant AI infrastructure capable of handling petabyte-scale data.
- Model Optimization: Develop and deploy advanced machine learning models, focusing on latency reduction and inference optimization.
- R&D Leadership: Spearhead research into emerging technologies, including Large Language Models (LLMs) and reinforcement learning.
- Code Review & Mentorship: Provide technical guidance to junior engineers and conduct rigorous code reviews to ensure maintainability and security.
- Deployment: Manage the end-to-end CI/CD pipeline for AI models, ensuring seamless integration into production environments.
- Strategy: Identify technical risks and opportunities for innovation within the 2026 technology stack.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Mathematics, or a related technical field.
- Experience: 5+ years of professional experience in machine learning engineering or AI research.
- Technical Skills: Expert proficiency in Python, TensorFlow, PyTorch, and CUDA.
- System Design: Strong understanding of distributed systems, microservices, and cloud architecture (AWS/GCP).
- Soft Skills: Excellent communication skills, with the ability to translate complex technical concepts to non-technical stakeholders.
- Innovation: Demonstrated track record of patentable innovations or publications in top-tier AI conferences.