Job Description
We are at the forefront of the AI revolution. At Quantum Leap Innovations, we are building the intelligent infrastructure of tomorrow. We are seeking a visionary Senior AI/ML Architect to lead the development of our next-generation generative AI platform for 2026 and beyond.
In this role, you will not just write code; you will define the architectural paradigms that will power enterprise-level AI solutions. You will bridge the gap between cutting-edge research and production-grade scalability. If you are driven by complexity and want to shape the future of intelligent systems, this is your opportunity.
Why Join Us?
- Work with state-of-the-art Large Language Models (LLMs) and Transformers.
- Competitive compensation package including equity.
- Flexible remote-first culture with top-tier equipment.
Responsibilities
- Architect Scalable AI Systems: Design and implement robust, distributed ML architectures capable of handling high-throughput data pipelines and inference workloads.
- Lead Model Development: Spearhead the research and deployment of generative AI models, focusing on NLP, computer vision, and multi-modal learning.
- Optimize Performance: Continuously improve model latency, accuracy, and resource efficiency in cloud environments (AWS/GCP).
- Mentorship & Culture: Guide a team of talented engineers and data scientists, fostering a culture of technical excellence and innovation.
- Technical Strategy: Define the technical roadmap for AI initiatives, evaluating emerging technologies like LLM fine-tuning and RAG (Retrieval-Augmented Generation).
- Security & Compliance: Implement best practices for model security, data privacy, and ethical AI usage.
Qualifications
- Experience: 8+ years in software engineering, with at least 5 years specifically in AI/ML architecture and MLOps.
- Technical Stack: Expert proficiency in Python, PyTorch, TensorFlow, and C++.
- Systems: Deep understanding of distributed systems, microservices, containerization (Docker/Kubernetes), and cloud infrastructure.
- AI Expertise: Proven experience building, fine-tuning, and deploying LLMs (e.g., GPT, Llama) and RAG architectures.
- Education: Master’s degree or PhD in Computer Science, Statistics, Mathematics, or a related technical field.
- Communication: Exceptional ability to translate complex technical concepts into actionable business strategies for stakeholders.