Job Description
Are you ready to architect the future of intelligent systems?
Quantum Leap Dynamics is pioneering the next generation of Artificial General Intelligence (AGI) and advanced neural interfaces. As a Senior AI Architect, you will lead the strategic design and implementation of scalable machine learning infrastructure for our 2026 roadmap. We are looking for a visionary technologist who thrives in a fast-paced, high-stakes environment and possesses the expertise to bridge the gap between theoretical research and production-grade software.
Why Join Us?
- Work on cutting-edge projects that redefine the boundaries of AI.
- Competitive compensation package including equity options.
- Flexible remote-first policy with a hub in San Francisco.
If you are ready to push the boundaries of what is possible in machine learning, we want to hear from you.
Responsibilities
- Design and architect scalable end-to-end machine learning pipelines for large-scale data processing and model training.
- Lead the research and development of novel algorithms to improve model accuracy, efficiency, and fairness.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate business requirements into technical solutions.
- Optimize existing models for inference speed and resource utilization on cloud-native environments.
- Establish best practices for MLOps, including version control, CI/CD, and model monitoring.
- Provide technical mentorship and guidance to junior engineers and data scientists.
- Stay abreast of the latest advancements in deep learning, NLP, and reinforcement learning.
Qualifications
- Master’s or Ph.D. in Computer Science, Mathematics, or a related technical field with a focus on Artificial Intelligence.
- Minimum of 5+ years of professional experience in designing and deploying production ML systems.
- Expert proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
- Strong experience with distributed computing systems (e.g., Apache Spark, Ray) and cloud platforms (AWS, GCP, or Azure).
- Proven track record of leading technical projects from conception to deployment.
- Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
- Familiarity with ethical AI principles and responsible AI development practices.