Job Description
Are you ready to define the technological landscape of 2026? Nexus Future Tech is seeking a visionary Senior AI Architect to lead our next-generation research division. We are building the infrastructure for tomorrow, today, and we need a technical leader who thrives on ambiguity and innovation.
In this pivotal role, you will not just manage code; you will architect the neural networks and algorithms that will power our global ecosystem. If you are obsessed with scalability, ethics in AI, and building systems that outperform expectations, we want to hear from you.
Why Join Us?
- Future-Ready Impact: Work on blue-sky projects that define the roadmap for 2026 and beyond.
- Competitive Compensation: Base salary of $180k - $250k plus equity and performance bonuses.
- Unlimited PTO: We trust our experts to manage their own time.
- Top-Tier Tools: Access to the latest hardware (GPUs) and cloud infrastructure.
The Role
As a Senior AI Architect, you will bridge the gap between theoretical research and production-grade deployment. You will lead a team of brilliant engineers and data scientists, setting the technical direction for our core AI products.
Responsibilities
- Design and implement scalable, distributed AI architectures for complex enterprise solutions.
- Lead a high-performing team of ML engineers and data scientists to drive project delivery.
- Collaborate with product leaders to translate business goals into technical roadmaps.
- Ensure model reliability, scalability, and ethical compliance across all deployments.
- Research and evaluate emerging technologies to keep our stack ahead of the curve.
- Mentor junior developers and conduct technical code reviews to maintain high engineering standards.
Qualifications
- Master’s degree in Computer Science, Mathematics, or a related field (PhD preferred).
- 7+ years of experience in software engineering and machine learning architecture.
- Deep expertise in Python, TensorFlow, PyTorch, and Hugging Face libraries.
- Proven experience designing MLOps pipelines and CI/CD workflows for ML models.
- Strong understanding of distributed systems, cloud architecture (AWS/GCP/Azure), and Kubernetes.
- Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.