Job Description
Quantum Nexus is at the forefront of the next technological revolution. We are looking for a visionary Senior AI Engineer to lead the architectural design of our core AI infrastructure, specifically targeting the technological milestones of 2026.
In this pivotal role, you will not just implement existing models but define the future of our generative AI capabilities. You will work in a high-performance environment where innovation is the standard and your code will impact millions of users globally.
Why Join Us?
- Work with state-of-the-art hardware and software stacks.
- Competitive equity package and benefits.
- Flexible remote-first culture with HQ in the heart of Silicon Valley.
The Role
We are seeking an expert to bridge the gap between theoretical AI research and production-grade engineering. You will own the longevity and scalability of our neural networks.
Responsibilities
- Architect and deploy scalable machine learning pipelines capable of handling petabyte-scale data.
- Lead the research and implementation of next-generation Large Language Models (LLMs) aligned with 2026 industry standards.
- Optimize model inference speed and reduce latency for real-time applications.
- Collaborate with product managers and data scientists to translate business requirements into technical AI solutions.
- Mentor junior engineers and establish best practices for code review and deployment.
- Ensure the ethical use of AI and maintain strict data privacy protocols.
Qualifications
- Master’s or PhD degree in Computer Science, Artificial Intelligence, or a related technical field.
- Minimum of 5+ years of experience in machine learning engineering, with at least 2 years in a leadership or senior technical role.
- Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Proven track record of deploying successful AI models into production environments.
- Strong understanding of distributed systems, cloud infrastructure (AWS/GCP/Azure), and containerization (Docker/Kubernetes).
- Experience with MLOps tools and CI/CD pipelines.