Job Description
Are you ready to define the technological landscape of 2026? Nexus Future Labs is looking for a visionary Senior AI Architect to lead our next-generation research initiatives. In this pivotal role, you will not just build AI models; you will architect the infrastructure that powers the autonomous systems of tomorrow. Join a team of elite engineers and data scientists dedicated to pushing the boundaries of Generative AI, Large Language Models (LLMs), and ethical machine learning.
We are looking for a pioneer who thrives in ambiguity and possesses the technical prowess to transform theoretical research into scalable, production-ready solutions. If you are passionate about the future of technology and want to leave a lasting impact on the industry, this is your opportunity.
Responsibilities
- Lead Strategic Architecture: Design and oversee the end-to-end architecture for complex AI systems, ensuring scalability, security, and high performance.
- Model Development: Spearhead the research and implementation of cutting-edge Generative AI and Large Language Model technologies.
- Technical Leadership: Mentor a team of talented data scientists and engineers, conducting code reviews and establishing best practices for AI development.
- Innovation & Research: Stay ahead of industry trends to integrate emerging technologies (e.g., neuromorphic computing, advanced NLP) into our core product roadmap.
- System Optimization: Optimize existing models for inference speed and reduce latency in real-time applications.
- Ethical AI Compliance: Ensure all AI deployments adhere to strict ethical guidelines and bias mitigation strategies.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related field.
- Experience: 7+ years of experience in software engineering with a focus on AI/ML, including at least 3 years in a senior or lead architectural role.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and experience with distributed computing frameworks (e.g., Apache Spark, Kubernetes).
- Domain Knowledge: Deep understanding of Natural Language Processing (NLP), Transformer architectures, and Reinforcement Learning.
- Problem Solving: Exceptional ability to solve complex, unstructured problems and translate business requirements into technical solutions.
- Communication: Excellent verbal and written communication skills, capable of presenting technical concepts to non-technical stakeholders.