Job Description
Are you ready to shape the technological landscape of 2026 and beyond? Nebula Innovations is seeking a visionary Senior AI Architect to lead our next-generation autonomous systems. We are building the infrastructure that will define the future of human-machine interaction, and we need a technical leader who thrives on complexity and innovation.
In this role, you will bridge the gap between theoretical research and production-grade deployment. You will architect scalable deep learning models that power our core products, ensuring they are robust, efficient, and ethically sound. If you are passionate about pushing the boundaries of Artificial General Intelligence (AGI) and possess a deep understanding of neural architectures, we want to hear from you.
Why Join Us?
- Work on cutting-edge projects with a world-class engineering team.
- Competitive compensation package including equity.
- Flexible remote-first culture with state-of-the-art equipment.
Responsibilities
- Design, train, and deploy state-of-the-art deep learning models for natural language processing and computer vision.
- Optimize inference pipelines to ensure sub-millisecond latency for real-time applications.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to define technical requirements.
- Research and implement novel architectural patterns to improve model accuracy and efficiency.
- Mentor junior engineers and conduct code reviews to maintain high technical standards.
- Ensure AI systems are interpretable, fair, and aligned with safety guidelines.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related technical field.
- 5+ years of professional experience in machine learning or artificial intelligence engineering.
- Extensive experience with Python, PyTorch, and TensorFlow.
- Deep knowledge of Transformer architectures, LLMs, and generative models.
- Proven track record of deploying large-scale models to cloud environments (AWS, GCP, or Azure).
- Strong understanding of distributed systems, MLOps, and data engineering principles.