Job Description
Join Nexus Horizon Labs, a pioneering force in next-generation artificial intelligence. We are building the foundational technologies that will define the landscape of 2026 and beyond. As a Senior AI Research Engineer, you will bridge the gap between theoretical breakthroughs and scalable production systems, working on projects that push the boundaries of what is possible with Large Language Models (LLMs) and generative AI.
We are looking for a visionary engineer who thrives in ambiguity and possesses a deep passion for the future of tech. You will not just write code; you will architect the intelligence of tomorrow. If you are ready to lead the charge in the AI revolution, we want to hear from you.
Why Join Us?
- Work on cutting-edge generative models.
- Competitive compensation and equity package.
- Flexible remote-first culture.
- Access to state-of-the-art compute resources.
Responsibilities
- Design and implement state-of-the-art machine learning algorithms and neural network architectures.
- Lead the research and development of scalable AI solutions, specifically focusing on multimodal models.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate research into production-ready applications.
- Mentor junior engineers and researchers, fostering a culture of technical excellence and innovation.
- Optimize existing models for speed, accuracy, and energy efficiency.
- Stay abreast of the latest academic research and industry trends to continuously improve our technology stack.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Machine Learning, or a related quantitative field.
- 5+ years of professional experience in machine learning research or applied AI development.
- Extensive experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX.
- Strong proficiency in Python and C++.
- Proven track record of publishing research in top-tier conferences (NeurIPS, ICML, ICLR) or deploying high-impact models.
- Experience with distributed computing and cloud platforms (AWS, GCP, or Azure).