Job Description
Shape the Future of Intelligence
We are Quantum Leap Systems, a pioneering force in Generative AI and Next-Gen Computing. As we look toward the technological landscape of 2026, we are seeking a visionary Senior AI Engineer to lead our core research division. You won't just be writing code; you will architect the neural networks that will power the next decade of human-machine interaction.
Why Join Us?
- Next-Gen Impact: Work on projects that define the future of AI, specifically targeting the 2026 technological roadmap.
- Unlimited PTO: We believe in work-life balance and autonomy.
- Top-Tier Equity: Competitive stock options in a high-growth unicorn environment.
- State-of-the-Art Hardware: Access to cutting-edge GPU clusters and quantum simulation tools.
Role Overview
In this high-visibility role, you will bridge the gap between theoretical research and production-grade deployment. You will lead a team of elite engineers to build scalable, fault-tolerant AI systems capable of processing petabytes of data in real-time.
Responsibilities
- Architect Advanced Models: Design and implement state-of-the-art Deep Learning architectures, specifically focusing on LLMs and multimodal systems for the 2026 era.
- Lead R&D Initiatives: Spearhead research into novel AI techniques, pushing the boundaries of what is possible in neural computation.
- Optimize Performance: Engineer highly efficient data pipelines and model optimization strategies to reduce latency and resource consumption.
- Production Deployment: Oversee the CI/CD pipelines for deploying AI models to cloud infrastructure (AWS/Azure/GCP) ensuring 99.99% uptime.
- Mentorship: Guide and mentor junior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Strategic Planning: Collaborate with product leadership to translate business goals into technical AI roadmaps.
Qualifications
- Education: MS or PhD in Computer Science, Mathematics, Statistics, or a related field.
- Experience: 5+ years of professional experience in AI/ML engineering with a proven track record of shipping production models.
- Technical Stack: Deep expertise in Python, TensorFlow, PyTorch, and Hugging Face Transformers.
- Language Model Expertise: Strong background in NLP, including fine-tuning LLMs and implementing Retrieval-Augmented Generation (RAG).
- Cloud Mastery: Experience with cloud-native ML services and containerization technologies (Docker, Kubernetes).
- Problem Solving: Ability to tackle complex, ambiguous problems with creative, data-driven solutions.