Job Description
The Opportunity: Are you ready to build the technology of tomorrow, today? Nexus Future Labs is seeking a visionary Senior AI Architect to lead our R&D division focusing on the "2026 Vision" roadmap. In this pivotal role, you will architect next-generation generative AI systems, autonomous agents, and spatial computing interfaces that will define the landscape of the future. We are looking for a technical leader who thrives on ambiguity and is passionate about pushing the boundaries of what is possible in Artificial Intelligence.
Why Join Us? We offer a competitive compensation package, equity opportunities, and a remote-first culture that encourages innovation. You will work alongside world-class engineers and researchers to solve the most complex challenges in the tech industry.
Responsibilities
- Architect & Design: Lead the architectural design and implementation of proprietary Large Language Models (LLMs) and Generative AI frameworks for the 2026 product suite.
- Roadmap Leadership: Define the technical strategy for AI integration across all platforms, ensuring scalability, security, and performance.
- Model Optimization: Oversee the fine-tuning and deployment of machine learning models on cloud infrastructure, reducing latency and maximizing inference efficiency.
- Cross-Functional Collaboration: Partner with product managers, designers, and engineers to translate complex AI capabilities into intuitive user experiences.
- Mentorship: Mentor junior data scientists and engineers, fostering a culture of continuous learning and technical excellence within the team.
- Research & Innovation: Stay ahead of industry trends, evaluating emerging technologies like Quantum AI and Neuromorphic computing for potential integration.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 5+ years of professional experience in Machine Learning Engineering, with at least 2 years in a leadership or senior architectural role.
- Programming: Proficiency in Python, C++, and experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX.
- AI Expertise: Strong background in Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- Cloud Proficiency: Extensive experience deploying models on AWS, GCP, or Azure using containerization technologies (Docker, Kubernetes).
- Soft Skills: Exceptional problem-solving abilities, excellent communication skills, and a track record of delivering high-impact projects.