Job Description
Are you ready to define the future of intelligence?
Nexus Horizon is pioneering the Project 2026 initiative, a bold leap into the next generation of artificial general intelligence. We are seeking a visionary Senior AI Research Engineer to lead the architectural design and implementation of our proprietary large-scale model ecosystem. If you thrive in a high-performance environment and want to solve problems that seem impossible today, this is your opportunity to build the foundation for tomorrow.
Why Nexus Horizon?
- Impactful Work: Directly contribute to the evolution of AGI.
- Elite Team: Collaborate with world-class researchers and engineers.
- Future-Proof: Shape the roadmap for the 2026 product launch.
Join us in San Francisco and be at the forefront of technological revolution.
Responsibilities
- Architect and implement novel deep learning architectures tailored for Project 2026's specific performance requirements.
- Conduct cutting-edge research to improve model efficiency, accuracy, and scalability in low-latency environments.
- Optimize existing inference pipelines using advanced quantization and pruning techniques.
- Collaborate with cross-functional teams (Product, Data Science, and Engineering) to translate research into production-ready applications.
- Mentor junior researchers and foster a culture of innovation and technical excellence within the team.
- Stay abreast of the latest developments in NLP, Computer Vision, and Reinforcement Learning to integrate state-of-the-art methodologies.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, Physics, or a related technical field.
- Minimum of 5+ years of hands-on experience in deep learning, machine learning, or AI research.
- Expert proficiency in Python and major ML frameworks (PyTorch, TensorFlow, or JAX).
- Strong mathematical background, specifically in Linear Algebra, Calculus, and Probability Theory.
- Proven track record of publishing in top-tier conferences (NeurIPS, ICML, ACL, ICLR) or shipping high-impact models.
- Experience with cloud infrastructure (AWS, GCP, or Azure) and distributed computing systems.