Job Description
Join the vanguard of technological innovation with Nebula Innovations. We are seeking a visionary Senior AI Architect to lead our Project 2026, a cutting-edge initiative aimed at revolutionizing the future of generative AI and autonomous systems. If you are passionate about architecting scalable solutions and defining the next generation of intelligent software, this is your opportunity to shape the future.
In this pivotal role, you will bridge the gap between theoretical AI research and production-grade engineering, ensuring our systems are not only robust but also ethically sound and future-proof. You will work closely with a world-class team of data scientists, engineers, and product managers to deploy state-of-the-art machine learning models that solve real-world problems.
Responsibilities
- System Architecture: Design and oversee the end-to-end architecture of complex AI systems, ensuring scalability, security, and high performance.
- Model Integration: Lead the integration of advanced machine learning models into our core product suite, optimizing for latency and accuracy.
- Technical Leadership: Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence within the Project 2026 team.
- Prototyping: Prototype and validate new AI paradigms, experimenting with the latest frameworks and hardware accelerators.
- Stakeholder Communication: Translate complex technical concepts into clear strategies for non-technical stakeholders and executive leadership.
- Infrastructure: Collaborate with DevOps teams to build and maintain the cloud infrastructure necessary for training and inference.
Qualifications
- Education: Master’s or PhD degree in Computer Science, Mathematics, or a related field, with a focus on AI/ML.
- Experience: 8+ years of experience in software engineering, with at least 4 years specifically focused on AI/ML architecture and deployment.
- Technical Skills: Proficiency in Python, PyTorch or TensorFlow, and experience with large language models (LLMs) and generative AI.
- Cloud Expertise: Deep understanding of cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Problem Solving: Demonstrated ability to troubleshoot complex system issues and optimize performance under tight constraints.
- Soft Skills: Exceptional communication skills, with the ability to lead cross-functional teams and drive projects from conception to delivery.