Job Description
We are on the cusp of a technological revolution, and we are looking for a visionary Senior AI Architect to lead our efforts in building the systems that will define the 2026 era of intelligent computing. At Nebula Dynamics, we don't just predict the future; we engineer it.
In this role, you will be responsible for designing scalable, robust, and ethical artificial intelligence systems that push the boundaries of what is possible. You will work closely with cross-functional teams to translate complex business requirements into cutting-edge technical solutions. If you are passionate about the future of AI and want to leave a lasting impact on the industry, we want to hear from you.
Why Join Us?
- Competitive salary and equity package.
- Flexible remote-first policy with a focus on output.
- Access to the latest hardware and cloud infrastructure.
- Professional development and continuous learning opportunities.
Responsibilities
- Architect and implement end-to-end AI solutions designed for the 2026 landscape, including large language models and generative AI frameworks.
- Lead the technical strategy for our machine learning infrastructure, ensuring scalability, security, and high performance.
- Collaborate with data scientists and engineers to optimize model training pipelines and reduce inference latency.
- Establish best practices for code quality, testing, and deployment within the AI lifecycle.
- Mentor junior developers and conduct technical architecture reviews.
- Stay ahead of industry trends in AI ethics, regulatory compliance, and emerging technologies.
Qualifications
- Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related field (or equivalent practical experience).
- Minimum of 7+ years of experience in software engineering, with at least 4 years specifically in AI/ML architecture.
- Deep expertise in Python, TensorFlow, PyTorch, and cloud-native architectures (AWS/GCP/Azure).
- Proven track record of deploying production-grade AI models that handle high-scale traffic.
- Strong understanding of MLOps, data pipelines, and model versioning strategies.
- Excellent communication skills with the ability to translate complex technical concepts for non-technical stakeholders.