Job Description
The Future is Now. Nexus Future Systems is pioneering the next generation of artificial intelligence. As a Lead AI Research Scientist within the 2026 Initiative, you will be at the forefront of developing proprietary neural architectures designed to revolutionize autonomous decision-making and quantum integration.
We are looking for a visionary individual who thrives in ambiguity and is passionate about pushing the boundaries of what is possible. If you are ready to architect the algorithms that will define the technological landscape of 2026 and beyond, we want to hear from you.
Responsibilities
- Architect the 2026 AI Roadmap: Define and execute the technical vision for our core AI research, focusing on next-gen Large Language Models and predictive analytics.
- Lead High-Impact Research: Spearhead complex research projects, publishing findings in top-tier academic journals and industry conferences.
- Team Mentorship: Guide and mentor a team of junior data scientists and ML engineers, fostering a culture of innovation and continuous learning.
- Prototype Development: Build and deploy scalable proof-of-concept models that demonstrate the feasibility of future state technologies.
- Collaborate Across Disciplines: Partner with product managers, engineers, and domain experts to translate research breakthroughs into tangible product features.
- Algorithm Optimization: Continuously optimize model performance, reducing latency and increasing accuracy for real-time applications.
Qualifications
- Education: Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Experience: 5+ years of experience in leading AI research teams or developing advanced machine learning systems at a top-tier tech company.
- Technical Proficiency: Deep expertise in Python, PyTorch, TensorFlow, and distributed computing frameworks.
- Knowledge: Strong understanding of Deep Learning, Natural Language Processing (NLP), and Reinforcement Learning.
- Problem Solving: Demonstrated ability to solve ambiguous, high-complexity problems with innovative solutions.
- Communication: Excellent written and verbal communication skills, with the ability to present complex technical concepts to non-technical stakeholders.
- Certifications: Experience with cloud platforms (AWS, GCP, Azure) and MLOps practices is a plus.