Job Description
Are you ready to define the technological landscape of 2026?
Nexus Horizon Systems is seeking a visionary Senior AI Architect to spearhead our next-generation neural network infrastructure. As we bridge the gap between today's AI and the intelligent systems of tomorrow, we need a leader who thrives on complexity and innovation. You will be instrumental in deploying cutting-edge machine learning models that power our core products, ensuring scalability and ethical AI implementation.
In this role, you will not just follow trends; you will set them. We are building the operating system for the year 2026, and we need a technical expert to guide our engineering team through the next evolution of artificial intelligence.
Responsibilities
- Lead Architectural Design: Design and implement scalable AI/ML infrastructure capable of handling high-volume data streams for 2026-scale applications.
- Research & Development: Spearhead research into Generative AI, Large Language Models (LLMs), and reinforcement learning to push the boundaries of current technology.
- System Optimization: Optimize existing models for latency, throughput, and resource efficiency to ensure seamless user experiences.
- Ethical AI Oversight: Establish and enforce guidelines for responsible AI development, ensuring fairness, transparency, and safety in automated decision-making.
- Team Mentorship: Mentor junior engineers and data scientists, conducting code reviews and technical architecture discussions to elevate the team's standard of excellence.
- Collaboration: Work closely with product managers and stakeholders to translate complex technical requirements into actionable engineering roadmaps.
Qualifications
- Education: Master’s degree in Computer Science, Data Science, or a related field (PhD preferred) with 5+ years of professional experience.
- Technical Expertise: Deep proficiency in Python, C++, and Java with extensive experience using frameworks such as PyTorch, TensorFlow, or JAX.
- Machine Learning Mastery: Proven track record of deploying end-to-end ML pipelines and working with NLP, Computer Vision, or Time-Series forecasting.
- Cloud Proficiency: Hands-on experience with cloud platforms (AWS, Azure, or GCP) and containerization technologies (Docker, Kubernetes).
- Problem Solving: Exceptional analytical skills with the ability to debug complex system-level issues and optimize performance bottlenecks.
- Communication: Excellent verbal and written communication skills, capable of explaining complex technical concepts to non-technical stakeholders.