Job Description
Are you ready to architect the future of intelligence? Nexus Horizon Systems is seeking a visionary Lead AI Research Engineer to spearhead our 'Year 2026' initiative. In this pivotal role, you will bridge the gap between theoretical breakthroughs and scalable production systems, helping us define the technological landscape for the next decade.
We are not just building models; we are building the infrastructure for a post-silicon era of computing. If you are passionate about pushing the boundaries of Generative AI, Quantum Machine Learning, and Neural Interfaces, we want to hear from you.
Why Join Us?
- Future-Proofing: Work on projects directly aligned with the 2026 technological roadmap.
- Impact: Your work will directly influence billions of users globally.
- Culture: A diverse, high-performance team of engineers, ethicists, and futurists.
Responsibilities
- Strategic R&D Leadership: Define and execute the technical vision for the 2026 AI ecosystem, focusing on next-generation Large Language Models and autonomous agents.
- Model Architecture: Design and optimize deep neural architectures that exceed current performance benchmarks in reasoning and adaptability.
- Prototyping & Validation: Build rapid prototypes to validate novel AI concepts before scaling them to production environments.
- Team Mentorship: Cultivate a high-performance engineering culture by mentoring junior researchers and conducting technical workshops.
- Cross-Functional Collaboration: Partner with product, security, and legal teams to ensure ethical AI deployment and scalability.
- Patent & Publication: Lead efforts to publish cutting-edge research and secure patents for proprietary algorithms.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Mathematics, Statistics, or a related field with a focus on Artificial Intelligence.
- Experience: 5+ years of experience in machine learning research, with at least 2 years in a leadership or senior engineering role.
- Technical Mastery: Deep expertise in Deep Learning frameworks (PyTorch, TensorFlow) and distributed computing systems.
- Programming: Proficiency in Python, C++, and familiarity with GPU acceleration technologies (CUDA).
- Problem Solving: Demonstrated ability to solve complex, unstructured problems in high-dimensional data spaces.
- Communication: Exceptional ability to communicate complex technical concepts to both technical and non-technical stakeholders.