Job Description
Join Nexus Horizon Inc., a forward-thinking leader in generative AI and autonomous systems, as our Senior AI Architect. We are building the technology stack for the year 2026 and beyond, and we need a visionary engineer to define our core machine learning infrastructure.
In this pivotal role, you will bridge the gap between theoretical research and scalable production systems. You will lead the architectural design for our next-generation AI models, ensuring they are robust, efficient, and ready to handle the complexities of the future web.
As a key member of our elite engineering team, you will collaborate with world-class researchers and product strategists to deliver AI solutions that redefine user experiences.
- Competitive Salary: $180k - $250k base plus performance bonuses.
- Equity Package: Generous stock options to share in our growth.
- Flexible Work: Hybrid model supporting remote and on-site collaboration.
- Continuous Learning: Access to cutting-edge conferences and research grants.
Responsibilities
- Architect and design scalable machine learning infrastructure capable of handling high-volume data streams.
- Lead the end-to-end development lifecycle of advanced AI models, including training, fine-tuning, and deployment.
- Collaborate with data science teams to translate research concepts into production-ready code.
- Implement best practices for MLOps, ensuring model reproducibility and monitoring.
- Define technical roadmaps for AI capabilities, specifically aligning with our 2026 product vision.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence and innovation.
- Conduct rigorous code reviews and performance optimization to ensure system stability.
Qualifications
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- 7+ years of professional experience in machine learning engineering and software development.
- Deep expertise in Python, TensorFlow, PyTorch, and Scikit-learn.
- Strong experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Proven track record of deploying large-scale AI models in production environments.
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.
- Experience with Generative AI, Large Language Models (LLMs), or Computer Vision is a plus.