Job Description
Are you ready to shape the technological landscape of 2026? Nexus Core Systems is seeking a visionary Future AI Lead to spearhead our next-generation research and development initiatives. In this pivotal role, you will define the architectural roadmap for our proprietary large language models and autonomous agents, ensuring we remain at the forefront of the AI revolution.
We are not just building software; we are constructing the cognitive infrastructure of the future. If you possess a deep understanding of Generative AI, System Architecture, and a passion for solving complex problems that will define the next decade of technology, we want to hear from you.
Why Join Us?
- Work on high-impact projects that will define the AI standards of 2026 and beyond.
- Collaborate with a world-class team of researchers and engineers.
- Competitive compensation package including equity and health benefits.
Responsibilities
- Architect and design scalable, high-performance large language model (LLM) infrastructures optimized for inference speed and accuracy.
- Lead the technical vision for our 2026 roadmap, identifying emerging AI trends such as Multimodal Learning and Reasoning Agents.
- Oversee the end-to-end training pipeline, from data curation and fine-tuning to deployment and monitoring.
- Mentor and guide a team of senior ML engineers and data scientists, fostering a culture of innovation and technical excellence.
- Establish rigorous evaluation frameworks to ensure model safety, ethical alignment, and compliance with emerging regulations.
- Drive cross-functional collaboration between R&D, Product, and Engineering teams to translate research into commercial applications.
Qualifications
- PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related quantitative field.
- 10+ years of experience in machine learning, deep learning, or natural language processing (NLP).
- Proven track record of leading AI research teams and delivering production-grade AI systems at scale.
- Deep expertise in PyTorch, TensorFlow, or JAX, and experience with distributed training frameworks.
- Strong background in reinforcement learning, attention mechanisms, and transformer architectures.
- Excellent communication skills with the ability to translate complex technical concepts for diverse stakeholders.