Job Description
We are not just building software; we are architecting the future of intelligence. Join Quantum Horizon AI as an AI Research Engineer and help define the technological landscape of 2026 and beyond.
In this pivotal role, you will bridge the gap between theoretical research and practical application, developing cutting-edge Large Language Models (LLMs) and autonomous agents that will revolutionize how businesses interact with data. If you are a visionary engineer passionate about the intersection of deep learning and ethical AI, we want to hear from you.
Why Join Us?
- Work on next-generation generative AI systems.
- Competitive compensation and equity package.
- Flexible remote-first culture with a hub in the heart of San Francisco.
- Access to state-of-the-art compute infrastructure.
Responsibilities
- Design and implement scalable machine learning architectures for large-scale production environments.
- Research and fine-tune state-of-the-art transformer models (e.g., GPT, Llama) to improve reasoning, coding, and multimodal capabilities.
- Optimize model inference speed and reduce latency using techniques like quantization and distillation.
- Collaborate with product teams to translate complex AI capabilities into user-friendly features.
- Ensure all AI systems adhere to strict ethical guidelines, safety protocols, and data privacy regulations.
- Contribute to the open-source community and publish research findings to establish thought leadership.
Qualifications
- Master’s or Ph.D. in Computer Science, Machine Learning, or a related technical field.
- 5+ years of professional experience in AI/ML engineering, with a strong focus on Deep Learning and Natural Language Processing (NLP).
- Expert proficiency in Python, PyTorch, and TensorFlow.
- Deep understanding of vector databases, RAG (Retrieval-Augmented Generation), and LLM deployment.
- Strong problem-solving skills and the ability to navigate ambiguity in fast-paced environments.
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.