Job Description
We are at the forefront of technological evolution, defining the landscape for 2026 and beyond. QuantumLeap Innovations is seeking a visionary Senior Generative AI Engineer to architect the next generation of intelligent systems. If you are passionate about pushing the boundaries of what is possible with Large Language Models (LLMs) and Generative Adversarial Networks (GANs), we want to hear from you.
As a key member of our elite R&D team, you will bridge the gap between theoretical research and production-ready applications, ensuring our AI solutions are scalable, ethical, and revolutionary.
Responsibilities
- Model Architecture: Design and implement cutting-edge generative AI architectures, including advanced Transformers and diffusion models, optimized for high-performance inference.
- Optimization: Reduce inference latency and improve model throughput in real-time production environments to support millions of users.
- Research & Development: Stay ahead of the curve on emerging AI trends to integrate breakthroughs into our product suite before the market adopts them.
- Deployment: Manage the full CI/CD pipeline for AI models, utilizing cloud infrastructure (AWS/GCP) and containerization technologies (Docker/Kubernetes).
- Collaboration: Partner closely with data scientists and product managers to translate complex research into tangible, user-centric AI products.
- Ethical AI: Implement rigorous testing and validation protocols to ensure fairness, transparency, and safety in AI outputs.
Qualifications
- Education: MS or PhD in Computer Science, Mathematics, Statistics, or a related field (or equivalent professional experience in AI engineering).
- Experience: 5+ years of professional experience in machine learning engineering, deep learning, or data science.
- Tools: Proficiency in Python, PyTorch, TensorFlow, and CUDA programming.
- Frameworks: Deep understanding of Hugging Face Transformers, LangChain, or similar state-of-the-art NLP frameworks.
- Cloud Expertise: Proven track record of deploying ML models at scale in cloud environments (AWS, Azure, or GCP).
- Problem Solving: Exceptional analytical skills with a focus on solving complex mathematical and computational problems.