Job Description
We are on a mission to engineer the intelligent infrastructure of the year 2026 and beyond. Quantum Horizon AI is seeking a visionary Senior Artificial Intelligence Engineer to lead the development of next-generation Generative AI systems. You will have the opportunity to work with state-of-the-art Large Language Models (LLMs) and scalable neural architectures to solve complex problems that define the future of technology.
In this pivotal role, you will bridge the gap between theoretical AI research and production-grade engineering. You will build systems that are not only high-performing but also ethical, explainable, and robust. If you are passionate about shaping the trajectory of AI and want to work in a culture of innovation, we want to hear from you.
Responsibilities
- Design, develop, and deploy advanced Machine Learning models, with a specific focus on Generative AI and Natural Language Processing (NLP).
- Optimize and fine-tune pre-trained models (e.g., GPT, LLaMA) for specific enterprise use cases to ensure high accuracy and low latency.
- Architect and maintain scalable MLOps pipelines for model training, validation, and continuous deployment.
- Collaborate with product managers and data scientists to define AI requirements and translate them into technical specifications.
- Ensure all AI systems comply with ethical guidelines, data privacy regulations (GDPR/CCPA), and bias mitigation standards.
- Mentor junior engineers and conduct code reviews to maintain high technical standards across the AI team.
Qualifications
- Master’s degree or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
- 5+ years of professional experience in AI/ML engineering, with a proven track record of deploying production-ready models.
- Strong proficiency in Python, PyTorch, TensorFlow, or JAX.
- Deep understanding of deep learning architectures, specifically Transformers and Attention mechanisms.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Familiarity with vector databases and RAG (Retrieval-Augmented Generation) architectures.