Job Description
We are at the precipice of a new technological era, and Nexus Future Systems is leading the charge toward the year 2026. We are looking for a visionary AI Architect to design the neural infrastructure of tomorrow. In this role, you will not just build models; you will define the architectural standards for next-generation Generative AI and Autonomous Systems.
As we prepare for the next evolution of artificial intelligence, we need a leader who understands the nuances of Large Language Models (LLMs), reinforcement learning, and scalable distributed systems. If you are passionate about pushing the boundaries of what machines can learn and create, this is your opportunity to shape the future.
Responsibilities
- Architect and deploy state-of-the-art generative AI models and Large Language Models (LLMs) optimized for enterprise scalability.
- Design robust MLOps pipelines to ensure continuous integration, deployment, and monitoring of AI models.
- Lead the research and implementation of novel algorithms for natural language understanding and generation.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate complex requirements into technical solutions.
- Optimize model performance, latency, and accuracy to meet production-grade reliability standards.
- Stay ahead of industry trends in AI safety, ethics, and regulation to ensure responsible AI deployment.
Qualifications
- Master’s or PhD in Computer Science, Machine Learning, or a related technical field (or equivalent practical experience).
- Extensive experience programming in Python with deep knowledge of frameworks such as PyTorch, TensorFlow, or JAX.
- Proven track record of building and deploying production-level machine learning models at scale.
- Strong understanding of transformer architectures, fine-tuning strategies, and RAG (Retrieval-Augmented Generation).
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.