Job Description
Shape the Future of Intelligence
QuantumLeap Systems is pioneering the breakthrough technologies required for the year 2026 and beyond. We are seeking a visionary Next-Gen AI Solutions Architect to lead the design and implementation of our cutting-edge Large Language Models and autonomous agent systems.
In this pivotal role, you will bridge the gap between theoretical AI research and scalable enterprise infrastructure. You will be responsible for defining the architectural standards that will power the next generation of human-machine interaction.
Why Join Us?
- Work on projects that define the AI landscape for the mid-2020s.
- Competitive compensation and equity packages.
- Flexible remote-first culture with a hub in San Francisco.
Are you ready to build the systems of tomorrow?
Responsibilities
- Design and deploy scalable, fault-tolerant AI infrastructure for large-scale distributed systems.
- Lead research initiatives into emerging AI paradigms, specifically focusing on Multimodal Learning and Agentic workflows.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate complex AI concepts into robust product features.
- Establish best practices for model training, evaluation, and deployment to ensure high performance and ethical AI compliance.
- Optimize existing models for inference speed and cost efficiency, targeting sub-millisecond latency where possible.
- Conduct technical mentorship and code reviews to foster a culture of innovation within the engineering team.
Qualifications
- Master’s degree in Computer Science, Artificial Intelligence, or a related technical field (PhD preferred).
- 5+ years of experience in machine learning engineering, with at least 2 years leading architectural decisions in AI systems.
- Strong proficiency in Python, PyTorch, TensorFlow, and Hugging Face Transformers.
- Deep understanding of Natural Language Processing (NLP) and Large Language Model (LLM) architecture.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Demonstrated ability to handle high-dimensional data and implement complex algorithms efficiently.