Job Description
We are at the precipice of the next industrial revolution, and Nexus Future Labs is seeking a visionary Lead AI Research Scientist to architect the neural architectures that will define the future of intelligence by 2026. In this pivotal role, you will spearhead the development of next-generation Artificial General Intelligence (AGI) systems, pushing the boundaries of deep learning, natural language processing, and autonomous decision-making.
Join a world-class team of engineers and data scientists dedicated to solving humanity's most complex challenges through advanced technology. You will have the autonomy to explore uncharted territories in machine learning, the resources to build state-of-the-art infrastructure, and the impact to shape the trajectory of technology for the next decade.
Responsibilities
- Define and execute the long-term R&D roadmap for AI advancements, specifically targeting milestones for the 2026 deployment cycle.
- Lead a high-performing team of researchers and engineers, fostering a culture of innovation, scientific rigor, and creativity.
- Design and prototype cutting-edge deep learning models, including transformers, reinforcement learning agents, and multimodal systems.
- Publish groundbreaking research in top-tier conferences (NeurIPS, ICML, ICLR) and contribute to the open-source community.
- Collaborate closely with product and engineering teams to translate theoretical research into scalable, production-ready AI products.
- Identify emerging trends in AI, including quantum machine learning and neuromorphic computing, and integrate them into our research stack.
Qualifications
- PhD, Master’s degree in Computer Science, Mathematics, Physics, or a related field with a focus on AI/ML.
- 10+ years of experience in research and development, with at least 5 years in a leadership or senior research scientist role.
- Deep expertise in machine learning frameworks (PyTorch, TensorFlow, JAX) and distributed computing systems.
- Proven track record of publishing high-impact papers and delivering complex AI systems from concept to deployment.
- Strong programming skills in Python, C++, and Rust.
- Experience with large-scale language models (LLMs), generative AI, or computer vision is highly preferred.
- Demonstrated ability to think strategically about the ethical implications of AI and implement responsible AI principles.