Job Description
We are at the forefront of the technological revolution, building the infrastructure for the year 2026 and beyond. Quantum Leap Technologies is seeking a visionary Senior AI/ML Architect to lead our next-generation research initiatives.
In this role, you will not just adapt to the future; you will define it. You will design scalable, ethical, and high-performance AI systems that solve complex global challenges. If you are passionate about Generative AI, Large Language Models (LLMs), and the intersection of human cognition and machine intelligence, we want to hear from you.
Why join us?
- Work with state-of-the-art hardware and software stacks.
- Competitive equity package and salary.
- Flexible remote-first culture with a hub in SF.
Be part of the team that sets the standard for artificial intelligence in the coming decade.
Responsibilities
- Architect and deploy end-to-end machine learning pipelines for production environments.
- Lead research in advanced Deep Learning architectures, specifically Transformers and Diffusion models.
- Optimize model inference latency and resource efficiency to support real-time applications.
- Collaborate with cross-functional teams (Data Science, Product, Engineering) to translate business requirements into technical AI solutions.
- Establish best practices for MLOps, model monitoring, and ethical AI governance.
- Present research findings and architectural designs to technical and non-technical stakeholders.
Qualifications
- Master’s or Ph.D. in Computer Science, Mathematics, or a related quantitative field.
- 5+ years of professional experience in AI/ML engineering, with at least 2 years in a lead or architect role.
- Deep proficiency in Python, PyTorch, or TensorFlow.
- Extensive experience with LLMs, RAG (Retrieval-Augmented Generation), and vector databases.
- Strong understanding of distributed systems, cloud architecture (AWS/Azure/GCP), and containerization (Docker/Kubernetes).
- Experience with MLOps tools (MLflow, Airflow, Kubeflow) and data orchestration.