Job Description
Are you ready to define the future of autonomous intelligence?
Nexus Dynamics is seeking a visionary Senior AI Architect to spearhead Project 2026, our flagship initiative to revolutionize predictive infrastructure. You will not just build models; you will architect the backbone of the next generation of intelligent systems.
In this pivotal role, you will bridge the gap between theoretical AI research and scalable, production-grade engineering. You will lead a team of elite engineers in designing neural networks capable of processing exabytes of data in real-time. If you are passionate about pushing the boundaries of what is possible with artificial general intelligence (AGI) and want to leave a lasting legacy in the tech industry, we want to meet you.
Why Join Nexus Dynamics?
- Impact: Directly influence the trajectory of AI development for the next decade.
- Compensation: Competitive base salary plus equity packages.
- Environment: Work in a state-of-the-art facility in the heart of San Francisco.
Join us in building the systems that will power the world of 2026 and beyond.
Responsibilities
- Architectural Leadership: Design and oversee the end-to-end architecture of complex AI systems, ensuring scalability, security, and performance.
- Model Development: Lead the research and implementation of cutting-edge deep learning models, specifically focusing on Transformer architectures and reinforcement learning.
- Technical Strategy: Define the technical roadmap for Project 2026, identifying emerging technologies and integrating them into our core infrastructure.
- Team Mentorship: Mentor junior engineers and data scientists, conducting code reviews, and fostering a culture of continuous learning and innovation.
- Performance Optimization: Optimize existing models for inference speed and resource efficiency, reducing latency in high-throughput environments.
- Stakeholder Collaboration: Collaborate with product managers and business stakeholders to translate complex technical requirements into actionable engineering goals.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, or a related technical field from a top-tier institution.
- Experience: Minimum of 8 years of experience in software engineering, with at least 4 years specifically focused on AI/ML architecture.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and distributed computing frameworks (e.g., Kubernetes, Spark).
- Problem Solving: Demonstrated ability to solve complex, ambiguous problems and make high-impact technical decisions under pressure.
- Leadership: Proven track record of leading high-performing engineering teams and managing cross-functional projects.
- Communication: Exceptional verbal and written communication skills, capable of explaining complex technical concepts to non-technical audiences.