Job Description
We are seeking a visionary Senior AI Architect to lead our research division dedicated to the 2026 Technological Horizon. Nexus Future Systems is pioneering the next generation of synthetic intelligence, and we need a technical leader to bridge the gap between current machine learning capabilities and the speculative architectures of the near future.
In this role, you will not just maintain existing systems; you will design the foundational blueprints for General Artificial Intelligence (AGI) and Neuromorphic Computing. You will work with a cross-functional team of futurists, data scientists, and hardware engineers to build scalable, ethical, and highly efficient AI models designed for the demands of 2026 and beyond.
Why Join Us?
- Impact at Scale: Shape the trajectory of human-machine interaction.
- R&D Focus: Work on bleeding-edge problems without the constraints of legacy infrastructure.
- Top-Tier Compensation: Comprehensive package including equity and performance bonuses.
- Flexible Environment: Hybrid work model based in the heart of NYC.
Responsibilities
- Architect and implement scalable deep learning models tailored for the 2026 computing ecosystem.
- Design novel neural network architectures capable of real-time reasoning and self-correction.
- Lead the evaluation of emerging hardware accelerators (e.g., quantum-classical hybrid chips) for AI inference.
- Mentor a team of junior data scientists and ML engineers, fostering a culture of innovation and rigorous testing.
- Collaborate with product teams to define the roadmap for AI-driven consumer and enterprise solutions.
- Ensure all AI systems adhere to the highest standards of data privacy, bias mitigation, and ethical AI governance.
Qualifications
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- 10+ years of experience in machine learning, deep learning, and software engineering.
- Proven track record of deploying production-grade AI systems at scale.
- Expertise in Python, PyTorch, TensorFlow, and C++.
- Strong understanding of distributed systems, cloud infrastructure (AWS/GCP), and edge computing.
- Experience with generative models, reinforcement learning, or multimodal AI systems is highly preferred.