Job Description
Shape the Future of Intelligence.
Are you ready to define the technological landscape of tomorrow? At Horizon 2026 Solutions, we are not just building software; we are architecting the very fabric of the future. We are seeking a visionary Lead AI Architect to spearhead our breakthrough initiatives in Generative AI, Autonomous Systems, and Quantum-Ready Machine Learning models.
In this high-impact role, you will bridge the gap between theoretical AI research and scalable, production-grade engineering. You will lead a team of elite engineers, pushing the boundaries of what is possible in Large Language Models (LLMs), computer vision, and predictive analytics. If you are driven by innovation and want to leave a legacy in the tech industry, this is your opportunity to lead the charge.
Why Join Us?
- Work on cutting-edge AI infrastructure that will define the 2026 era.
- Competitive compensation and equity package.
- Flexible remote-first culture with premium benefits.
Responsibilities
- Architect Scalable AI Systems: Design and implement robust, scalable machine learning pipelines and neural network architectures capable of handling exabyte-scale data.
- Lead R&D in Generative AI: Spearhead research and development efforts in LLMs, diffusion models, and multi-modal AI to create industry-leading products.
- Technical Leadership: Mentor a diverse team of data scientists and engineers, fostering a culture of innovation, code excellence, and continuous learning.
- Strategic Roadmapping: Define the long-term technical vision for AI initiatives, ensuring alignment with business goals and emerging market trends.
- Model Optimization: Drive the optimization of model inference speed and accuracy, ensuring low-latency performance for real-time applications.
- Collaboration: Work closely with product managers and stakeholders to translate complex AI capabilities into user-centric solutions.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 8+ years of professional experience in software engineering and machine learning, with at least 3 years in a senior leadership or architectural role.
- Technical Expertise: Deep proficiency in Python, PyTorch, TensorFlow, and modern deep learning frameworks.
- AI Specialization: Extensive experience with Transformer architectures, fine-tuning LLMs (e.g., GPT-4, LLaMA), and MLOps practices.
- System Design: Strong ability to design distributed systems and cloud-native AI solutions (AWS, GCP, or Azure).
- Soft Skills: Exceptional communication skills with the ability to articulate complex technical concepts to non-technical stakeholders.