Job Description
Shape the Future with Project 2026
Nexus Horizon Technologies is at the forefront of the AI revolution, and we are currently recruiting for a visionary Senior AI Architect to lead Project 2026. This is a unique opportunity to design and deploy next-generation generative models that will redefine human-machine interaction in the enterprise sector.
In this role, you will not just write code; you will architect the backbone of our AI ecosystem. You will work closely with C-level executives and engineering leads to build systems that are not only scalable but ethically sound and transformative. If you are passionate about the intersection of quantum computing, large language models, and neural networks, this is your calling.
Why Join Us?
- Impactful Work: Directly influence the trajectory of AI development.
- Top-Tier Compensation: Competitive salary and equity package.
- Flexible Culture: Work from our SF headquarters or globally.
Responsibilities
- Design and oversee the architecture of the Project 2026 neural network infrastructure, ensuring high scalability and fault tolerance.
- Lead the R&D efforts in integrating Generative AI with legacy enterprise systems to drive operational efficiency.
- Collaborate with cross-functional teams to define technical requirements and deliver innovative AI solutions.
- Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
- Ensure all AI models comply with strict ethical guidelines, privacy regulations, and industry standards.
- Prioritize security and data integrity in all architectural decisions.
Qualifications
- Master’s or Ph.D. in Computer Science, Mathematics, or a related field, with a focus on Artificial Intelligence.
- 8+ years of professional experience in software engineering, with at least 5 years specifically in Machine Learning and Deep Learning.
- Expert proficiency in Python, PyTorch, TensorFlow, and modern Big Data technologies (e.g., Spark, Kafka).
- Strong understanding of Large Language Models (LLMs), fine-tuning, and prompt engineering.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.