Job Description
We are looking for a visionary Senior AI Architect to lead the next wave of generative intelligence at Nexus Horizon. As we stand on the precipice of the 2026 AI revolution, we need a technical leader to design, build, and deploy large-scale neural architectures that redefine human-machine interaction. You will not just write code; you will architect the cognitive frameworks of tomorrow.
Why Join Us?
- Work at the intersection of science and creativity.
- Competitive equity and stock options in a Series C funded unicorn.
- Top-tier benefits including unlimited PTO and comprehensive health coverage.
- Access to cutting-edge hardware and proprietary datasets.
If you are passionate about pushing the boundaries of Large Language Models (LLMs) and Computer Vision, this is your opportunity to shape the future.
Responsibilities
- Lead the end-to-end design and implementation of proprietary AI models, specifically focusing on Generative AI and LLM fine-tuning strategies.
- Architect scalable, high-performance data pipelines and infrastructure using cloud-native technologies (AWS/GCP) to handle petabytes of training data.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate complex research into production-ready features.
- Mentor junior engineers and researchers, fostering a culture of technical excellence and innovation.
- Optimize model inference speeds and reduce latency to ensure real-time user experiences.
- Stay abreast of the latest academic research and industry trends to implement state-of-the-art algorithms.
Qualifications
- Master’s or PhD in Computer Science, Machine Learning, Mathematics, or a related technical field.
- Minimum of 5+ years of professional experience in AI/ML engineering, with at least 2 years specifically in Generative AI or Deep Learning.
- Strong proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
- Proven experience with MLOps, CI/CD, and containerization technologies (Docker, Kubernetes).
- Deep understanding of NLP, Transformers, or Reinforcement Learning from Human Feedback (RLHF).
- Experience with model quantization, optimization, and serving at scale.