Job Description
Are you ready to define the technological landscape of the future? Nexus Future Labs is seeking a visionary Lead AI Research Scientist to spearhead our initiatives for the 2026 era. We are building the next generation of artificial general intelligence, and we need a leader who is passionate about pushing the boundaries of neural networks and machine learning.
As a key member of our elite R&D team, you will be responsible for architecting scalable AI systems that solve complex global problems. We offer a competitive compensation package, stock options, and the opportunity to work on cutting-edge projects that will shape the world in the years to come.
Why Join Us?
- Work on the forefront of Artificial Intelligence and Machine Learning.
- Competitive salary and equity packages.
- Flexible remote-first culture with state-of-the-art equipment.
- Opportunity to mentor the next generation of tech talent.
Responsibilities
- Lead the research and development of advanced machine learning models, focusing on Large Language Models (LLMs) and generative AI.
- Design and implement novel neural network architectures to improve model accuracy and efficiency.
- Collaborate with cross-functional teams to translate research findings into scalable production-ready software.
- Mentor junior researchers and data scientists, fostering a culture of innovation and technical excellence.
- Stay abreast of the latest academic research and industry trends to ensure our technology remains competitive.
- Optimize model inference speed and resource utilization to handle massive datasets.
- Define the technical roadmap for AI initiatives and drive the adoption of best practices in MLOps.
Qualifications
- PhD in Computer Science, Mathematics, or a related technical field (or equivalent extensive industry experience).
- Proven track record of publishing in top-tier conferences (NeurIPS, ICML, ACL, etc.) or shipping high-impact AI products.
- Expert proficiency in Python, PyTorch, and TensorFlow.
- Strong understanding of deep learning principles, natural language processing, and computer vision.
- Experience with distributed systems and cloud computing platforms (AWS, GCP, or Azure).
- Demonstrated ability to lead teams and manage complex projects from conception to deployment.
- Familiarity with ethical AI practices and bias mitigation techniques.