Job Description
Join the Architects of Tomorrow.
Horizon AI Systems is pioneering the next generation of artificial intelligence, and we are looking for a visionary Senior AI Architect to help define our roadmap for the 2026 landscape. This is not just a job; it is an opportunity to build the infrastructure that will power the future of enterprise intelligence.
In this role, you will bridge the gap between cutting-edge research and scalable production systems. You will lead architectural initiatives that push the boundaries of what is possible with Deep Learning and Generative AI, ensuring our solutions are robust, ethical, and scalable for global deployment.
Why join us?
- Future-Ready Tech Stack: Work with the latest in LLMs, Computer Vision, and Quantum-inspired algorithms.
- Competitive Compensation: $190k - $260k base salary + equity package.
- Impactful Work: Your code will directly influence how millions of users interact with AI in the near future.
Ready to architect the future? Apply today.
Responsibilities
- Design and deploy scalable, high-performance AI architectures for large-scale data processing and model inference.
- Lead technical strategy for the 2026 roadmap, identifying emerging trends in NLP, Computer Vision, and reinforcement learning.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence and innovation.
- Collaborate with cross-functional product teams to translate complex business requirements into technical specifications.
- Ensure system reliability, security, and compliance with industry standards (SOC2, GDPR).
- Optimize existing ML pipelines to reduce latency and improve cost-efficiency.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Artificial Intelligence, or a related technical field.
- Minimum of 7+ years of experience in software engineering and machine learning architecture.
- Deep expertise in Python, TensorFlow, PyTorch, and modern MLOps frameworks.
- Proven track record of designing and implementing production-grade AI systems at scale.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Strong understanding of neural network architectures and optimization techniques.