Job Description
We are pioneering the next generation of Artificial General Intelligence (AGI), aiming to redefine human-machine interaction by 2026. Nexus Future Systems is seeking a visionary Senior AI Architect to lead the technical strategy for our flagship reasoning engine. You will not just build models; you will architect the future of synthetic cognition.
In this high-impact role, you will be at the forefront of the AI revolution, working with a world-class team to solve the most complex challenges in machine learning, large-scale inference, and ethical alignment.
Why Join Us?
- Work on mission-critical projects that will shape the future of technology.
- Competitive compensation and equity package.
- State-of-the-art hardware infrastructure.
- Flexible remote-first culture with a hub in San Francisco.
Responsibilities
- Architect Scalable AI Systems: Design and deploy robust, scalable neural network architectures capable of handling petabyte-scale data.
- Lead Research Initiatives: Spearhead research in transformer models, reinforcement learning, and self-supervised learning to push the boundaries of AGI.
- Ethical AI Governance: Establish and enforce rigorous safety protocols and ethical guidelines to ensure AI alignment with human values.
- Model Optimization: Lead efforts in model pruning, quantization, and inference optimization to reduce latency and resource consumption.
- Technical Mentorship: Mentor junior data scientists and engineers, fostering a culture of continuous learning and innovation.
- Cross-Functional Collaboration: Partner with product and engineering teams to translate complex AI capabilities into user-friendly applications.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Mathematics, or a related field with a focus on Artificial Intelligence.
- Technical Expertise: Deep proficiency in Python, PyTorch, TensorFlow, and Hugging Face libraries.
- Experience: 5+ years of experience in deep learning, NLP, or computer vision, with a track record of deploying production-grade AI models.
- Problem Solving: Exceptional ability to tackle unstructured problems and develop novel algorithmic solutions.
- Communication: Excellent verbal and written communication skills, capable of presenting complex technical concepts to diverse stakeholders.
- Tools: Familiarity with cloud platforms (AWS, GCP, Azure) and MLOps tools (Docker, Kubernetes, MLflow).