Job Description
We are Apex Neural Systems, a pioneer in the field of Artificial General Intelligence (AGI). As we march towards the pivotal year of 2026, we are seeking a visionary AI Model Architect to lead the development of our next-generation foundation models.
In this role, you will not just write code; you will architect the cognitive framework of the future. You will be responsible for designing scalable, efficient, and ethical neural architectures that push the boundaries of what machines can understand and generate. If you are passionate about the intersection of neuroscience and computer science and want to define the roadmap for 2026, we want to hear from you.
Why join us?
- Future-Ready Environment: Work on cutting-edge projects that define the trajectory of AI for the next decade.
- Top-Tier Talent: Collaborate with world-class researchers and engineers.
- Competitive Compensation: Comprehensive benefits package including equity.
Join us in building the intelligent systems that will power the world of tomorrow.
Responsibilities
- Architect Design: Design and implement novel neural network architectures optimized for the specific demands of 2026 computing paradigms, including edge-AI and quantum-enhanced processing.
- Model Optimization: Lead initiatives to improve model inference speed, reduce computational costs, and enhance training efficiency using advanced quantization and pruning techniques.
- Research & Innovation: Conduct cutting-edge research in Large Language Models (LLMs), multimodal AI, and reinforcement learning to drive product innovation.
- Ethical AI: Implement robust safety protocols and alignment strategies to ensure AI outputs are fair, unbiased, and safe for deployment in critical sectors.
- Technical Leadership: Mentor junior engineers and data scientists, conducting code reviews and architectural reviews to maintain high technical standards.
- Cross-Functional Collaboration: Work closely with product managers, ethicists, and domain experts to translate complex requirements into technical solutions.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Mathematics, or a related field with a focus on AI/ML.
- Experience: Minimum of 5 years of professional experience in machine learning, deep learning, or AI research, with at least 2 years in a lead or architect role.
- Technical Skills: Deep proficiency in Python, PyTorch, TensorFlow, and distributed training frameworks.
- Domain Knowledge: Extensive knowledge of transformer models, attention mechanisms, and NLP.
- Problem Solving: Proven track record of solving complex technical challenges and optimizing large-scale systems.
- Communication: Excellent verbal and written communication skills, with the ability to explain complex concepts to diverse audiences.