Job Description
Join the Vanguard of Artificial Intelligence
Are you ready to define the landscape of Generative AI and Autonomous Systems for the year 2026 and beyond? Nexus Future Systems is seeking a visionary Senior AI Architect to lead our next-generation research initiatives. We are not just building software; we are architecting the future of human-machine interaction.
Why Join Us?
Work with a world-class team of engineers and data scientists pushing the boundaries of what is possible. You will have the autonomy to experiment with cutting-edge models, contribute to open-source communities, and directly impact the trajectory of global AI evolution.
Your Mission
As a Senior AI Architect, you will bridge the gap between theoretical research and production-grade deployment, ensuring our solutions are scalable, ethical, and revolutionary.
Responsibilities
- Architect Scalable Systems: Design and implement robust, high-performance AI infrastructure capable of handling petabyte-scale data processing.
- Model Development: Spearhead the development and fine-tuning of Large Language Models (LLMs) and multimodal AI agents for enterprise applications.
- R&D Leadership: Lead experimental research projects focusing on Reinforcement Learning from Human Feedback (RLHF) and ethical AI alignment.
- Production Deployment: Oversee the MLOps lifecycle, including CI/CD pipelines, model serving, and real-time inference optimization.
- Cross-Functional Collaboration: Partner with product managers and software engineers to integrate complex AI models into seamless user experiences.
- Technical Mentorship: Mentor junior data scientists and engineers, fostering a culture of continuous learning and innovation within the engineering team.
Qualifications
- Education: Ph.D. or M.S. in Computer Science, Machine Learning, Statistics, or a related quantitative field.
- Experience: Minimum 7+ years of experience in software engineering or machine learning, with at least 3 years in a senior architectural role.
- Technical Stack: Proficiency in Python, PyTorch, or TensorFlow; deep understanding of distributed systems (Kubernetes, Docker).
- AI Expertise: Proven track record of working with LLMs, NLP, or Computer Vision; experience with RAG (Retrieval-Augmented Generation) architectures.
- Problem Solving: Exceptional ability to deconstruct complex problems and deliver elegant, scalable solutions.
- Communication: Excellent verbal and written communication skills; ability to articulate technical concepts to non-technical stakeholders.