Job Description
Are you ready to architect the future of intelligence? Horizon 2026 Dynamics is a cutting-edge research firm pioneering the next wave of Generative AI and Quantum-Neural interfaces. We are looking for a visionary Senior AI Architect to join our elite 'Horizon 2026' initiative. In this role, you will not just build models; you will define the foundational architecture for the technologies that will drive global transformation in 2026 and beyond. You will work at the intersection of deep learning, distributed systems, and ethical AI governance, reporting directly to the Chief Technology Officer.
Responsibilities
- Lead Architectural Vision: Design and implement scalable, high-performance neural network architectures tailored for the Horizon 2026 ecosystem.
- R&D Leadership: Spearhead research initiatives to push the boundaries of Large Language Models (LLMs) and multimodal AI capabilities.
- System Optimization: Oversee the training infrastructure, ensuring efficient GPU utilization and low-latency inference for real-time applications.
- Code Review & Mentorship: Establish rigorous engineering standards, conduct deep-dive code reviews, and mentor junior engineers and data scientists.
- Strategic Roadmapping: Collaborate with product and engineering leadership to define technical roadmaps that align with the 2026 product launch schedule.
- Ethical AI Compliance: Ensure all deployed models adhere to strict ethical guidelines, bias mitigation protocols, and data privacy regulations.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, or a related quantitative field from a top-tier institution.
- Experience: 10+ years of experience in AI/ML engineering, with at least 5 years in a senior architectural or leadership role.
- Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, and CUDA. Experience with distributed training frameworks (Ray, Kubernetes).
- Algorithm Mastery: Proven track record of designing novel algorithms or improving state-of-the-art performance on benchmark datasets.
- Communication: Exceptional ability to translate complex technical concepts into clear strategic insights for non-technical stakeholders.
- Certifications: AWS Solutions Architect or Google Cloud Professional Machine Learning Engineer certification preferred.