Job Description
Are you ready to define the future of Artificial Intelligence?
Quantum Leap Dynamics is seeking a visionary Senior AI Engineer to join our elite research team in San Francisco. In this role, you will not just use existing tools; you will architect the neural architectures that will power our next generation of intelligent systems. We are building for 2026 and beyond, focusing on scalable, ethical, and highly performant machine learning models.
If you are passionate about pushing the boundaries of Deep Learning, Natural Language Processing, and Computer Vision, and you want to work in a high-impact environment where your code matters, we want to hear from you.
Responsibilities
- Architect and Develop: Design, train, and deploy advanced machine learning models, including Transformers and Large Language Models (LLMs), optimized for high throughput.
- Research & Innovation: Conduct cutting-edge research to solve complex problems in NLP, computer vision, or reinforcement learning, publishing findings where applicable.
- Model Optimization: Reduce inference latency and improve model accuracy through quantization, pruning, and efficient architecture design.
- Collaboration: Work closely with product managers and software engineers to integrate AI models seamlessly into production applications.
- Infrastructure: Manage the full ML lifecycle, from data ingestion and preprocessing to MLOps pipelines using tools like Kubernetes and Docker.
- Mentorship: Guide junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field with a focus on AI/ML.
- Experience: Minimum of 5 years of professional experience in AI/ML engineering roles.
- Technical Skills: Strong proficiency in Python, PyTorch, TensorFlow, or JAX. Deep understanding of statistical learning theory.
- Deployment: Proven experience deploying models to cloud environments (AWS, GCP, or Azure) and managing containerized workflows.
- Problem Solving: Ability to tackle ambiguous problems and derive scalable solutions in a fast-paced, startup environment.
- Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.