Job Description
The Future of Intelligence Starts Here.
Nexus Future Labs is pioneering the next generation of autonomous systems and generative AI. We are seeking a visionary Senior AI Architect to lead our research and development efforts for our 2026 roadmap. In this role, you will bridge the gap between theoretical machine learning breakthroughs and scalable production environments, defining how artificial intelligence integrates into daily life.
As a key member of our elite technical team, you will be responsible for architecting the core neural networks that power our next-generation products. We offer a competitive salary, equity packages, and the opportunity to work on cutting-edge technology that will define the technological landscape of the coming decade.
Responsibilities
- Architect Development: Design and implement robust, scalable, and secure AI/ML infrastructure capable of handling petabyte-scale data processing.
- Model Optimization: Lead the research and optimization of large language models (LLMs) and generative adversarial networks (GANs) to improve inference speed and accuracy.
- Technical Strategy: Define the long-term technical vision for AI adoption within the company, ensuring alignment with the 2026 strategic roadmap.
- R&D Leadership: Mentor a team of junior data scientists and engineers, fostering a culture of innovation and continuous learning.
- Cross-Functional Collaboration: Work closely with product managers, designers, and engineering teams to translate complex AI capabilities into user-friendly products.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Experience: 7+ years of experience in software engineering, with at least 4 years dedicated to AI/ML architecture and research.
- Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, or JAX. Experience with distributed computing frameworks (Kubernetes, Apache Spark).
- Domain Knowledge: Proven track record of deploying successful ML models in production environments.
- Soft Skills: Exceptional problem-solving abilities and excellent communication skills for technical stakeholder management.