Job Description
We are Quantum Dynamics, a cutting-edge research lab pioneering the technologies that will define the year 2026 and beyond. We are seeking a visionary Lead AI Architect to lead our initiative in pre-AGI systems and next-generation generative models.
In this role, you won't just be maintaining legacy code; you will be building the foundational infrastructure for the autonomous systems of tomorrow. You will work directly with our research team to bridge the gap between theoretical AI breakthroughs and scalable production systems. If you are obsessed with the future of Artificial General Intelligence and possess the technical prowess to execute it, we want to meet you.
Why Join Us?
- Future-Proof Technology: Work on architectures designed for the era of 2026.
- Unlimited PTO & Equity: Competitive compensation package reflecting your high-impact role.
- Remote-First Culture: Flexible work environment from anywhere in the US.
The Role
You will be the technical steward of our AI roadmap, responsible for the full lifecycle of our machine learning models, from data ingestion to deployment at scale.
Responsibilities
- Architect Next-Gen AI Systems: Design and implement scalable distributed systems for training and deploying Large Language Models (LLMs) and multimodal AI agents.
- Model Optimization: Lead efforts in model quantization, distillation, and fine-tuning to ensure low-latency inference for real-time applications.
- RAG Infrastructure: Build robust Retrieval-Augmented Generation pipelines to enhance model accuracy and reduce hallucinations.
- AI Ethics & Safety: Establish frameworks for AI safety, fairness, and transparency, ensuring our technology aligns with global standards.
- Technical Leadership: Mentor a team of senior engineers and data scientists, fostering a culture of innovation and continuous learning.
- Scalability Engineering: Optimize cloud infrastructure (AWS/Azure) to handle petabyte-scale datasets and high concurrency.
Qualifications
- Education: MS or PhD in Computer Science, Mathematics, or a related field.
- Experience: 7+ years of experience in software engineering, with at least 3 years specializing in Machine Learning and Deep Learning.
- Programming: Expert-level proficiency in Python and C++.
- Frameworks: Deep experience with PyTorch, TensorFlow, or JAX.
- Knowledge: Proven track record of implementing LLMs (GPT, LLaMA, Claude) and RAG architectures.
- Cloud: Strong background in cloud-native technologies (Kubernetes, Docker, Terraform).
- Soft Skills: Exceptional communication skills with the ability to translate complex technical concepts to non-technical stakeholders.