Job Description
Join the Future of Intelligence
QuantumBridge Systems is pioneering the Project 2026 initiative—a groundbreaking effort to define the next generation of artificial general intelligence. We are seeking a visionary Senior AI Research Engineer to architect scalable, ethical, and high-performance AI models capable of solving the complex challenges of tomorrow.
In this role, you will bridge the gap between theoretical research and practical deployment, working on cutting-edge Large Language Models (LLMs) and autonomous agent systems. If you are passionate about the trajectory of AI and want to build the infrastructure that powers the future, we want to hear from you.
Why join Project 2026?
- Work on technology that will define the industry standard for 2026 and beyond.
- Competitive compensation package including equity options.
- Access to top-tier compute resources and research facilities.
Key Objectives:
- Drive the architectural vision for our next-generation reasoning models.
- Optimize model inference for real-time, high-volume applications.
- Ensure AI safety, fairness, and alignment with human values.
Responsibilities
- Architect Development: Design and implement robust, scalable neural network architectures tailored for the 2026 roadmap, focusing on efficiency and accuracy.
- Model Optimization: Apply techniques such as quantization, pruning, and distillation to deploy massive models on edge devices without compromising performance.
- R&D Leadership: Conduct rigorous research experiments to push the boundaries of current LLM capabilities, including multimodal reasoning and code generation.
- Code Review & Mentorship: Lead code reviews for the research team, establish coding standards, and mentor junior engineers and data scientists.
- Ethical AI Implementation: Develop and integrate safety filters and alignment protocols to prevent bias and ensure responsible AI deployment.
- Collaboration: Partner with product teams to translate complex research findings into deployable product features.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Mathematics, or a related field, with a focus on Artificial Intelligence or Machine Learning.
- Experience: 5+ years of professional experience in AI/ML research or engineering, preferably in a senior capacity.
- Technical Stack: Proficiency in Python, PyTorch, or TensorFlow. Experience with distributed training frameworks (Ray, Horovod) is highly desirable.
- Research: A strong publication record (NeurIPS, ICML, ACL, etc.) or significant contributions to open-source AI projects.
- Problem Solving: Demonstrated ability to tackle ambiguous problems and derive innovative solutions under tight deadlines.
- Communication: Excellent written and verbal communication skills, capable of presenting complex technical concepts to non-technical stakeholders.