Job Description
Are you ready to define the trajectory of artificial intelligence for the year 2026 and beyond?
Nexus Horizon is at the forefront of the generative AI revolution. We are looking for a visionary AI Architect to lead our research and engineering division. In this pivotal role, you will not just adapt to the future of technology; you will architect it. You will build the frameworks, optimize the neural networks, and establish the ethical standards that will define human-machine interaction in the next decade.
If you possess a deep understanding of LLMs, large-scale data systems, and a passion for ethical AI, we want to hear from you.
Why Nexus Horizon?
- Work with the most advanced models available in 2026.
- Competitive equity package and top-tier benefits.
- Flexible remote/hybrid work environment.
Responsibilities
- Architect End-to-End AI Systems: Design scalable, fault-tolerant machine learning infrastructure capable of handling petabytes of data in real-time.
- Model Optimization: Lead initiatives to optimize transformer architectures for reduced latency and increased inference speed.
- Roadmap Strategy: Define the technical roadmap for 2026, identifying emerging technologies like Quantum AI integration and Neuromorphic computing.
- Team Leadership: Mentor a team of senior data scientists and ML engineers, fostering a culture of innovation and continuous learning.
- Ethical AI Implementation: Establish and enforce guidelines for bias mitigation and data privacy in all deployed models.
- Cross-Functional Collaboration: Partner with product and engineering teams to translate complex AI capabilities into user-friendly applications.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related field.
- Experience: 7+ years of experience in machine learning, deep learning, or AI engineering, with at least 3 years in a senior architectural role.
- Technical Mastery: Expert proficiency in Python, PyTorch, TensorFlow, and distributed computing frameworks (Kubernetes, Spark).
- LLM Expertise: Proven experience fine-tuning and deploying Large Language Models (e.g., GPT-4, LLaMA, Claude) for enterprise applications.
- System Design: Strong background in distributed systems, cloud architecture (AWS/GCP/Azure), and MLOps pipelines.
- Soft Skills: Exceptional communication skills with the ability to explain complex technical concepts to non-technical stakeholders.