Job Description
Are you ready to shape the future of autonomous intelligence?
Nexus Dynamics is at the forefront of the Horizon 2026 Initiative, a groundbreaking program dedicated to developing next-generation neural architectures that will redefine human-machine interaction. We are seeking a visionary Senior AI Architect to lead our engineering efforts in building scalable, ethical, and high-performance artificial intelligence systems.
In this pivotal role, you will bridge the gap between theoretical research and production-grade deployment. You will work with a world-class team of researchers and engineers to architect the systems that power the future of the web and beyond. If you are passionate about pushing the boundaries of what is possible with machine learning and want to leave a lasting legacy, we want to hear from you.
Why Join Us?
- Work on cutting-edge AI technologies with a tangible impact on society.
- Competitive compensation package with equity options.
- Flexible remote-first culture with state-of-the-art office amenities in San Francisco.
Responsibilities
- Design and implement scalable neural network architectures for large-scale language models and autonomous agents.
- Lead the architectural direction for the Horizon 2026 infrastructure, ensuring high availability and fault tolerance.
- Collaborate with cross-functional teams including researchers, product managers, and ethicists to align AI capabilities with business goals.
- Oversee the deployment of ML models to production environments, optimizing for inference speed and cost efficiency.
- Mentor junior engineers and architects, fostering a culture of continuous learning and innovation.
- Establish best practices for data privacy, security, and ethical AI usage within the organization.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related field with a focus on Artificial Intelligence.
- 10+ years of experience in software engineering and machine learning, with at least 5 years in a leadership or architectural role.
- Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Proven track record of shipping complex, high-performance ML systems to production.
- Strong understanding of distributed systems, cloud infrastructure (AWS/Azure/GCP), and containerization (Docker/Kubernetes).
- Experience with MLOps tools and version control systems (Git, GitLab).