Job Description
Shape the Future of Intelligence with Us
We are QuantumLeap Technologies, a pioneer in next-generation artificial intelligence. We are currently seeking a visionary Senior AI Architect to define our roadmap for 2026. If you are passionate about pushing the boundaries of Generative AI, Large Language Models, and Autonomous Systems, this is your opportunity to lead the charge.
In this role, you won't just write code; you will architect the cognitive infrastructure of our future products. We offer a competitive compensation package, equity opportunities, and the chance to work with a world-class team of researchers and engineers.
Why Join Us?
- Impactful Work: Build AI solutions that redefine industry standards.
- Future-Ready: Work on cutting-edge technologies relevant to the 2026 landscape.
- Competitive Compensation: $190k - $280k base salary plus equity.
What You'll Do
Responsibilities
- Architect and deploy scalable, high-performance AI models, focusing on Generative AI and LLMs.
- Lead the design and implementation of the 2026 AI strategy, ensuring alignment with business objectives.
- Optimize neural network architectures for speed, accuracy, and energy efficiency.
- Collaborate with cross-functional teams to integrate AI capabilities into consumer-facing products.
- Establish best practices for MLOps, data governance, and ethical AI usage.
- Research and evaluate emerging AI technologies to maintain a competitive edge.
Qualifications
Qualifications
- Master’s or Ph.D. in Computer Science, Machine Learning, or a related field (or equivalent experience).
- 5+ years of professional experience in AI/ML engineering, with a focus on deep learning frameworks.
- Strong proficiency in Python, PyTorch, TensorFlow, and C++.
- Deep understanding of Natural Language Processing (NLP) and Transformer architectures.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Proven track record of shipping complex machine learning products to production.
Skills
Python, PyTorch, TensorFlow, NLP, Machine Learning, Deep Learning, MLOps, AWS, GCP, Docker, Kubernetes, Transformer Models