Job Description
Are you ready to architect the future?
Nexus Horizon AI is at the forefront of defining the technological landscape for 2026 and beyond. We are seeking a visionary Lead AI Architect to spearhead the development of our next-generation autonomous systems and generative intelligence frameworks. This is not just a job; it is a mission to shape the ethical and functional future of AI.
In this role, you will bridge the gap between theoretical machine learning research and scalable, production-grade engineering. You will lead a world-class team of data scientists and engineers, ensuring our solutions are robust, secure, and ahead of the curve.
Why join us?
- Work on cutting-edge AI projects with real-world impact.
- Competitive compensation and equity packages.
- Flexible remote and hybrid work options.
- Access to state-of-the-art computing infrastructure.
Responsibilities
- Architectural Leadership: Design and implement the core architecture for large-scale AI models, focusing on scalability, fault tolerance, and low-latency inference.
- Technology Strategy: Evaluate and integrate emerging AI technologies (e.g., Neural Architecture Search, Federated Learning) to maintain a competitive edge.
- Team Mentorship: Guide junior engineers and data scientists, fostering a culture of innovation, continuous learning, and technical excellence.
- Model Optimization: Oversee the fine-tuning and optimization of Large Language Models (LLMs) for specific enterprise applications.
- Compliance & Ethics: Establish and enforce guidelines for AI safety, bias mitigation, and regulatory compliance (GDPR, AI Act).
- Collaboration: Partner with product managers and stakeholders to translate business requirements into technical roadmaps.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 7+ years of experience in software engineering, with at least 4 years specifically focused on Machine Learning and Deep Learning systems.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Deep understanding of distributed systems and cloud architectures (AWS, GCP, or Azure).
- Model Engineering: Proven track record of deploying and serving complex models in production environments (e.g., Kubernetes, Docker, Kubernetes).
- Leadership: Demonstrated experience leading high-performing engineering teams and managing technical projects from conception to delivery.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.