Job Description
Are you ready to define the intelligence of tomorrow?
Quantum Core Systems is pioneering the infrastructure for the autonomous era of 2026. We are seeking a visionary Senior AI Research Scientist to lead our R&D division in developing next-generation generative models and autonomous agents. You will be at the forefront of solving complex problems that will define the technological landscape of the coming years.
In this role, you will bridge the gap between cutting-edge academic research and production-scale deployment, ensuring our solutions are not only powerful but also scalable and ethical. If you are passionate about pushing the boundaries of what is possible with Artificial General Intelligence, we want to meet you.
Why Join Us?
- Work on mission-critical projects that impact the future of humanity.
- Competitive compensation package including equity and health benefits.
- Access to state-of-the-art compute resources and research tools.
- A collaborative and inclusive culture that values innovation.
Responsibilities
- Architect and train large-scale generative AI models optimized for enterprise and consumer applications.
- Research and implement novel techniques to enhance model reasoning, efficiency, and multimodal capabilities.
- Collaborate closely with product engineering teams to integrate AI solutions into real-world products.
- Mentor junior researchers and engineers, fostering a culture of technical excellence and continuous learning.
- Optimize model inference latency and reduce resource consumption for cost-effective deployment.
- Stay abreast of the latest developments in the AI field and contribute to internal technical blogs.
Qualifications
- PhD or Master’s degree in Computer Science, Machine Learning, or a related technical field.
- 5+ years of professional experience in Deep Learning, Natural Language Processing, or Computer Vision.
- Strong proficiency in Python, PyTorch, and TensorFlow.
- Proven track record of publishing research in top-tier conferences (NeurIPS, ICML, ACL, or equivalent).
- Experience with distributed computing frameworks (e.g., Apache Spark, Ray) and cloud infrastructure (AWS/GCP).
- Demonstrated ability to translate theoretical research into robust, production-ready code.