Job Description
Are you ready to define the future of Artificial Intelligence?
Quantum Leap AI is at the forefront of the 2026 tech revolution. We are looking for a visionary Senior AI Engineer to join our elite 'Visionary Track' team. In this pivotal role, you will architect the next generation of Generative AI models and autonomous systems.
We are not just building software; we are engineering the foundation for the next decade of human-machine interaction. If you thrive in fast-paced, high-impact environments and want to push the boundaries of what's possible with Large Language Models (LLMs) and Neural Networks, we want to hear from you.
Why Join Us?
- Work with state-of-the-art hardware and proprietary AI architectures.
- Competitive equity package and performance bonuses.
- Flexible remote-first policy with quarterly co-working retreats.
- Unlimited PTO and comprehensive health benefits.
Responsibilities
- Architect LLM Solutions: Design and deploy scalable, high-performance generative AI models tailored for enterprise applications.
- Prompt Engineering & Fine-Tuning: Develop advanced prompt engineering strategies and fine-tune open-source models (e.g., Llama 3, Mistral) for specific vertical domains.
- System Optimization: Optimize model inference latency and reduce token costs using techniques like quantization and distillation.
- Research & Innovation: Stay ahead of the curve with emerging research papers and implement cutting-edge techniques into production code.
- Collaboration: Partner with product managers and data scientists to translate complex business requirements into robust AI technical solutions.
- Mentorship: Lead and mentor junior engineers, conducting code reviews and technical workshops to foster a culture of excellence.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, or a related field (or equivalent practical experience).
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and experience with Hugging Face Transformers.
- Experience: Minimum 5 years of experience in AI/ML engineering, with a proven track record of deploying production-ready models.
- Domain Knowledge: Deep understanding of NLP, Natural Language Understanding (NLU), and RAG (Retrieval-Augmented Generation) architectures.
- Tools: Experience with cloud platforms (AWS/GCP/Azure) and containerization tools (Docker, Kubernetes).
- Communication: Excellent verbal and written communication skills, capable of explaining complex technical concepts to non-technical stakeholders.