Job Description
Shape the Future of Intelligence with Project 2026
Nebula Horizon Solutions is a pioneering force in next-generation computing. We are currently recruiting a visionary Senior AI Architect to lead our flagship initiative, Project 2026. This is not just a job; it is an opportunity to architect the neural networks that will define the next era of human-machine interaction.
In this high-impact role, you will be responsible for the end-to-end design of our proprietary machine learning infrastructure. You will work at the intersection of theoretical research and practical engineering, ensuring our systems are scalable, secure, and capable of processing petabytes of data in real-time.
Our Culture:
- Innovation First: We celebrate failure as a necessary step in the learning process.
- Global Impact: Your work will directly influence industries ranging from healthcare to autonomous transportation.
- Equity-First: We offer a competitive compensation package with significant equity opportunities.
Responsibilities
- Define the architectural vision for Project 2026, including the selection of core frameworks (PyTorch, TensorFlow) and hardware accelerators.
- Design and implement distributed machine learning pipelines capable of handling high-velocity data streams.
- Collaborate with cross-functional teams of data scientists, researchers, and product managers to translate business goals into technical solutions.
- Optimize existing models for latency, throughput, and memory efficiency.
- Mentor a team of mid-level engineers, providing technical guidance and fostering professional growth.
- Ensure rigorous testing, validation, and compliance with industry standards for AI ethics and safety.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related quantitative field.
- 8+ years of experience in software engineering with a specialization in Artificial Intelligence and Machine Learning.
- Deep expertise in Python, C++, and distributed systems architecture.
- Proven experience deploying large-scale LLMs and generative models to production environments.
- Familiarity with cloud infrastructure (AWS, GCP, or Azure) and container orchestration (Kubernetes).
- Strong problem-solving skills with the ability to navigate ambiguity and drive projects to completion.
- Excellent verbal and written communication skills.