Job Description
Join the Vanguard of Artificial Intelligence
Nexus Future Systems is seeking a visionary AI Architect 2026 to lead the next generation of intelligent solutions. As a pioneer in generative AI and machine learning infrastructure, we are building systems that define the future of human-computer interaction. In this role, you will not just implement existing technologies; you will architect the frameworks that drive our enterprise roadmap for the coming decade.
We are looking for a thought leader who thrives in ambiguity and possesses a deep understanding of the mathematical underpinnings of neural networks, coupled with the practical skills to deploy them at scale.
Responsibilities
- Architect Scalable AI Infrastructure: Design and implement robust, high-throughput machine learning pipelines and inference engines capable of handling billions of requests.
- Lead Research & Innovation: Spearhead research initiatives into emerging paradigms such as Large Language Models (LLMs), multimodal AI, and reinforcement learning.
- Model Optimization: Drive performance engineering to reduce latency and cost while maximizing model accuracy and efficiency.
- Ethical AI Governance: Establish and enforce guidelines for responsible AI development, ensuring fairness, transparency, and accountability in all deployed models.
- Tech Stack Evangelism: Mentor engineering teams, conduct code reviews, and establish best practices for MLOps and data governance.
- Strategic Planning: Collaborate with product leadership to translate complex business requirements into cutting-edge technical roadmaps.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Mathematics, or a related field with a focus on AI/ML.
- Experience: 5+ years of experience in software engineering with a specific focus on machine learning architecture and NLP/CV domains.
- Technical Proficiency: Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Cloud Mastery: Proven track record of deploying and managing AI workloads on major cloud providers (AWS, GCP, or Azure).
- MLOps: Experience with CI/CD pipelines, containerization (Docker/Kubernetes), and model serving frameworks (Triton, TorchServe).
- Problem Solving: Exceptional ability to debug complex distributed systems and optimize algorithmic performance.