Job Description
Join Nexus Horizon Labs as a Lead AI Architect and play a pivotal role in defining the technological backbone for our 2026 Horizon Initiative. We are not just building software; we are architecting the future of autonomous systems and predictive analytics. In this high-impact role, you will lead a world-class team of researchers and engineers to deploy scalable, ethically-driven AI models designed for the 2026 era.
As a key architect, you will bridge the gap between theoretical research and production-grade systems. You will ensure our infrastructure is future-proof, robust, and capable of handling the massive data throughput required by our upcoming global launch. If you are passionate about pushing the boundaries of what is possible with Large Language Models (LLMs) and Generative AI, and you want to leave a lasting legacy in the tech landscape, this is your opportunity.
Why Join Us?
- Shape the Future: Directly influence the roadmap for the 2026 Horizon product line.
- World-Class Team: Collaborate with Ph.D.-level scientists and industry veterans.
- Competitive Compensation: Top-tier salary and equity packages.
Responsibilities
- Design and implement scalable AI infrastructure capable of supporting the high-volume demands of the 2026 release cycle.
- Lead the research and development of proprietary Large Language Models (LLMs) tailored for enterprise applications.
- Mentor junior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Ensure the ethical deployment of AI, focusing on bias mitigation and transparency in algorithmic decision-making.
- Collaborate with cross-functional product teams to translate complex business requirements into technical architectures.
- Optimize model performance, latency, and cost-efficiency across distributed cloud environments.
- Define best practices for MLOps, CI/CD pipelines, and data governance.
Qualifications
- Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field.
- 10+ years of experience in AI/ML engineering, with at least 4 years in a lead or architectural role.
- Extensive hands-on experience with deep learning frameworks such as PyTorch or TensorFlow.
- Proven track record of deploying large-scale ML models in production environments (e.g., AWS, GCP, Azure).
- Strong expertise in Natural Language Processing (NLP) and Generative AI techniques.
- Experience with MLOps tools (e.g., Kubeflow, MLflow, Airflow).
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.