Job Description
Architecting the Future of Intelligence
At Nexus Horizon Labs, we are not just building software; we are engineering the fabric of tomorrow. We are seeking a visionary Senior AI Architect to lead our next-generation generative intelligence division. In this pivotal role, you will define the architectural standards for Large Language Models (LLMs) and autonomous agents that will define the technological landscape of 2026 and beyond.
As part of our elite technical team, you will bridge the gap between theoretical breakthroughs and scalable production systems. If you are passionate about pushing the boundaries of what is possible in AI and want to leave a lasting legacy in the industry, we want to hear from you.
Why Join Us?
- Work on cutting-edge AI research and deployment.
- Competitive compensation package and equity options.
- Flexible remote-first culture with state-of-the-art equipment.
- Opportunity to mentor the next generation of AI engineers.
Responsibilities
- Design and implement scalable machine learning infrastructure and pipelines for LLMs and neural networks.
- Lead the architectural strategy for integrating AI solutions into core product ecosystems.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to deliver high-impact features.
- Ensure model accuracy, performance, and ethical deployment standards are met.
- Mentor junior engineers and conduct code reviews to maintain high technical standards.
- Stay ahead of industry trends in AI, NLP, and computer vision.
Qualifications
- Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related technical field.
- Minimum of 5+ years of professional experience in Machine Learning Engineering or AI Architecture.
- Extensive experience with deep learning frameworks (PyTorch, TensorFlow, or JAX).
- Proven track record of deploying large-scale models to production environments.
- Strong proficiency in programming languages such as Python and C++.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Deep understanding of AI ethics, bias mitigation, and responsible AI practices.