Job Description
The Future is Now. At QuantumLeap Dynamics, we aren't just predicting the trends of 2026; we are building them. We are seeking a visionary Senior AI Architect to lead our core research division, focusing on next-generation generative models and autonomous agent systems.
In this pivotal role, you will bridge the gap between theoretical breakthroughs and production-grade engineering. You will be responsible for architecting the AI infrastructure that will power our clients' operations for the next decade. If you are passionate about the frontier of machine learning and want to leave a legacy in the tech landscape of 2026, this is your opportunity.
Why Join Us?
We offer equity, unlimited PTO, and a fully remote-first culture that respects your time. You will work alongside world-class researchers and engineers to solve problems that don't have answers yet.
Responsibilities
- Architect Next-Gen Systems: Design and implement scalable machine learning pipelines for Large Language Models (LLMs) and multi-modal agents intended for the 2026 market landscape.
- Research & Development: Lead internal research initiatives to explore novel architectures, optimizing for efficiency, accuracy, and inference speed.
- Model Optimization: Implement advanced quantization and pruning techniques to deploy models on edge devices and low-latency environments.
- Technical Leadership: Mentor junior engineers and data scientists, conducting code reviews and architectural workshops to maintain high engineering standards.
- Deployment & MLOps: Oversee the CI/CD pipeline for AI models, ensuring rigorous testing, monitoring, and rollback capabilities in production environments.
- Strategic Vision: Collaborate with product leaders to define the roadmap for AI-driven features, ensuring alignment with business goals.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field.
- 7+ years of professional experience in software engineering and machine learning.
- Expert proficiency in Python, PyTorch, and TensorFlow.
- Deep understanding of NLP, LLMs (Transformers, BERT, GPT architectures), and RAG systems.
- Experience with distributed systems, Kubernetes, and cloud platforms (AWS/GCP/Azure).
- Strong grasp of mathematical foundations, including linear algebra, calculus, and probability.
- Demonstrated ability to ship production-grade code and lead technical teams.