Job Description
Are you ready to architect the next generation of human-computer interaction? Nexus Future Labs is seeking a visionary Senior Synthetic Intelligence Architect to lead our 2026 roadmap. In this role, you will design the neural pathways and cognitive frameworks that power our next-generation AI agents, bridging the gap between advanced machine learning and human intuition.
We are looking for a thought leader who thrives on solving complex problems at the intersection of neuroscience, computer science, and quantum computing. You will be responsible for defining the architectural standards that will define our product suite for the coming decade.
Why join us?
We offer a competitive salary, stock options, and the opportunity to work in a cutting-edge environment where the impossible is just the beginning.
Responsibilities
- Architect Design: Design scalable, fault-tolerant neural network architectures for autonomous agents and predictive systems.
- R&D Leadership: Lead research initiatives into synthetic cognition, focusing on self-improvement algorithms and emotional intelligence simulation.
- System Optimization: Optimize model latency and inference speed for real-time cognitive processing.
- Cross-Functional Collaboration: Work closely with UX researchers and product managers to translate complex technical capabilities into user-centric features.
- Technical Mentorship: Mentor junior engineers and data scientists, fostering a culture of innovation and continuous learning.
- Future Proofing: Evaluate emerging technologies (e.g., neuromorphic chips, quantum annealing) and integrate them into our development pipeline.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Mathematics, Computational Neuroscience, or a related field.
- Experience: 7+ years of professional experience in AI/ML engineering, with at least 3 years in a senior or leadership role.
- Technical Skills: Deep expertise in PyTorch, TensorFlow, or JAX; proficiency in C++ for high-performance computing.
- Specialized Knowledge: Experience with Large Language Models (LLMs), Transformer architectures, or neuromorphic computing is highly preferred.
- Problem Solving: Proven track record of solving ambiguous problems and defining technical strategy from the ground up.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.