Job Description
Are you ready to shape the trajectory of artificial intelligence for the next decade? Nebula Dynamics is seeking a visionary Lead AI Architect to spearhead Project 2026—our ambitious initiative to redefine the boundaries of Generative AI and neural architecture.
In this high-impact role, you won't just write code; you will architect the future. We are looking for a technical leader who thrives in ambiguity and possesses an insatiable curiosity about what's possible when advanced machine learning meets scalable infrastructure.
Why Join Us?
- Next-Gen Impact: Work on the core technology that will power our clients' digital ecosystems by 2026 and beyond.
- Top-Tier Compensation: Competitive salary ($180k - $250k) plus performance bonuses and equity.
- Cutting-Edge Stack: Work with the latest in PyTorch, TensorFlow, and custom GPU clusters.
- Remote-First Culture: Enjoy the flexibility of working from anywhere in the US.
Join a team of world-class engineers and researchers dedicated to pushing the envelope of what AI can achieve.
Responsibilities
- Define and execute the technical roadmap for Project 2026, ensuring alignment with business objectives and long-term vision.
- Design and implement scalable, fault-tolerant machine learning pipelines capable of handling petabytes of data.
- Lead a team of senior engineers and researchers, providing mentorship and fostering a culture of innovation.
- Collaborate closely with product managers and stakeholders to translate complex technical concepts into user-centric solutions.
- Stay at the forefront of AI research, evaluating and integrating emerging technologies (LLMs, Diffusion Models, Reinforcement Learning) into production environments.
Qualifications
- Master’s or Ph.D. in Computer Science, Machine Learning, or a related quantitative field (or equivalent professional experience).
- Minimum of 7+ years of experience in software engineering with a strong focus on AI/ML systems.
- Deep proficiency in Python, C++, and experience with major ML frameworks (PyTorch, TensorFlow, JAX).
- Proven track record of deploying large-scale ML models into production, managing model lifecycle, and optimizing for inference speed and cost.
- Strong understanding of distributed systems, cloud architecture (AWS/GCP), and containerization technologies (Docker/Kubernetes).