Job Description
We are pioneering the technology landscape of 2026. At Nexus Future Labs, we are not just predicting the future; we are architecting it. We are seeking a visionary Advanced AI Researcher & Strategist to lead our R&D division, focusing on generative AI, predictive modeling, and the ethical frameworks that will define the next decade of human-machine interaction.
In this role, you will bridge the gap between theoretical AI research and practical application, ensuring our solutions are scalable, robust, and ahead of the curve. If you are passionate about the trajectory of technology and want to shape the infrastructure of the future, we want to meet you.
Responsibilities
- Lead 2026 Strategic Roadmap: Define and execute the long-term R&D strategy for our flagship AI products, ensuring alignment with our vision for the year 2026.
- Pioneering Research: Spearhead research into Large Language Models (LLMs), neural architecture search, and next-gen generative AI technologies.
- Model Optimization: Develop and optimize deep learning models for high-performance deployment in real-world enterprise environments.
- Technical Mentorship: Cultivate a high-performance engineering culture by mentoring junior researchers and providing technical guidance on complex architectural decisions.
- Cross-Functional Collaboration: Partner with product managers, engineers, and data scientists to translate research breakthroughs into market-ready features.
- Ethical AI Governance: Establish and enforce guidelines for responsible AI, ensuring transparency and fairness in our algorithms.
Qualifications
- Education: Master’s or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Experience: 5+ years of professional experience in AI/ML research or engineering roles, with a proven track record of published papers or significant patents.
- Technical Proficiency: Deep expertise in Python, PyTorch, TensorFlow, or JAX, with experience in distributed training frameworks.
- Domain Knowledge: Strong understanding of Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- Problem Solving: Demonstrated ability to tackle ambiguous, complex problems and derive innovative solutions.
- Communication: Exceptional written and verbal communication skills, capable of presenting complex technical concepts to diverse stakeholders.