Job Description
Are you ready to engineer the intelligence of tomorrow? Nexus Horizon Labs is pioneering the frontier of next-generation Artificial Intelligence, specifically targeting breakthroughs for the 2026 era. We are looking for a visionary Senior AI Research Scientist to lead our advanced neural architecture research and scalable generative model initiatives.
In this role, you won't just write code; you will define the paradigms of autonomous systems and human-AI interaction. If you thrive on complexity and have a passion for pushing the boundaries of what is possible in machine learning, we want to meet you.
Responsibilities
- Lead Research Initiatives: Spearhead the development of cutting-edge deep learning architectures, focusing on scalability and efficiency for 2026 computing paradigms.
- Model Optimization: Design and implement novel algorithms to reduce inference latency and enhance model accuracy in real-time applications.
- Interdisciplinary Collaboration: Partner with hardware engineers and data scientists to integrate AI models into edge computing environments.
- Prototype Development: Build and iterate on Proof-of-Concept (PoC) systems demonstrating future capabilities in Natural Language Processing and Computer Vision.
- Technical Mentorship: Guide a team of junior researchers and engineers, fostering a culture of innovation and continuous learning.
- Publish & Patent: Author high-impact research papers and contribute to our intellectual property portfolio in AI ethics and safety.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Mathematics, or a related field, with a focus on Artificial Intelligence or Machine Learning.
- Experience: Minimum of 5+ years of professional experience in AI research, with a track record of publishing in top-tier conferences (NeurIPS, ICML, ICLR).
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and experience with large-scale distributed training frameworks.
- Domain Expertise: Deep understanding of Transformer models, Reinforcement Learning, or Generative Adversarial Networks (GANs).
- Problem Solving: Demonstrated ability to tackle ambiguous, high-complexity problems and deliver robust, scalable solutions.
- Soft Skills: Excellent communication skills with the ability to translate complex technical concepts for diverse stakeholders.