Job Description
We are on a mission to define the technological landscape of 2026 and beyond. QuantumLeap Industries is seeking a visionary Senior AI Architect to lead our breakthrough initiatives in Generative AI and autonomous systems. If you are passionate about building scalable, ethical, and transformative artificial intelligence, this is your opportunity to shape the future.
As a key member of our R&D division, you will bridge the gap between theoretical research and production-grade engineering, ensuring our AI models are robust, efficient, and ready for the demands of the next decade.
Why Join Us?
- Impactful Work: Build AI systems that redefine industry standards.
- Future-Forward: Work on cutting-edge projects scoped for the 2026 era.
- Competitive Compensation: Top-tier salary and equity packages.
- Remote-First Culture: Flexible work environment in the heart of SF.
Responsibilities
- Design and architect scalable machine learning infrastructure tailored for 2026 workloads, including Large Language Models (LLMs) and edge AI.
- Lead the end-to-end lifecycle of AI model development, from data ingestion and preprocessing to training, fine-tuning, and deployment.
- Optimize model inference speeds and reduce computational costs using advanced quantization and distributed training techniques.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to define technical roadmaps and AI product requirements.
- Establish best practices for MLOps, ensuring reproducibility, monitoring, and automated retraining pipelines.
- Advocate for ethical AI practices and ensure compliance with emerging regulations and safety standards.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field (PhD preferred).
- 7+ years of professional experience in software engineering, with at least 3 years dedicated to machine learning or AI architecture.
- Deep expertise in Python, PyTorch, TensorFlow, and modern deep learning frameworks.
- Proven experience designing distributed systems capable of handling petabyte-scale datasets.
- Strong understanding of cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Experience implementing RAG (Retrieval-Augmented Generation) pipelines and vector databases.
- Excellent communication skills with the ability to translate complex technical concepts for diverse audiences.