Job Description
Are you ready to build the future of intelligence?
Apex Neural Systems is pioneering The 2026 Initiative, a groundbreaking project focused on developing next-generation autonomous AI agents capable of complex, multi-step reasoning. We are looking for a visionary Senior Artificial Intelligence Architect to lead the technical strategy and execution of this transformative roadmap. If you are passionate about pushing the boundaries of what is possible with Large Language Models (LLMs) and generative AI, this is your chance to define the industry standard.
In this pivotal role, you will bridge the gap between theoretical research and scalable production engineering, ensuring our solutions are not only cutting-edge but also secure and efficient.
Responsibilities
- Lead Strategic Architecture: Design and implement the core architecture for autonomous AI agents, focusing on scalability, fault tolerance, and real-time learning capabilities.
- Model Optimization: Oversee the fine-tuning and optimization of large-scale transformer models to ensure high performance and low latency in production environments.
- R&D Leadership: Spearhead research initiatives to explore emerging technologies in reinforcement learning and multimodal AI integration.
- Team Mentorship: Mentor a high-performing team of ML engineers and data scientists, fostering a culture of innovation and continuous learning.
- Production Deployment: Collaborate with DevOps teams to deploy models to cloud infrastructure, implementing rigorous monitoring and A/B testing frameworks.
- Stakeholder Communication: Translate complex technical concepts into clear insights for executive leadership and product stakeholders.
- Risk Management: Identify potential biases and security vulnerabilities in AI systems, implementing mitigation strategies proactively.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Machine Learning, Statistics, or a related quantitative field.
- Experience: 7+ years of experience in software engineering, with at least 4 years focused specifically on Artificial Intelligence and Deep Learning.
- Technical Skills: Deep expertise in PyTorch, TensorFlow, or JAX; experience with distributed training frameworks (Ray, Horovod).
- Project 2026 Relevance: Demonstrated ability to work on long-term, forward-looking projects and adapt to rapidly evolving technical landscapes.
- Programming: Proficiency in Python and experience with containerization technologies (Docker, Kubernetes).
- Soft Skills: Exceptional problem-solving abilities and excellent verbal and written communication skills.
- Certifications: AWS Certified Machine Learning – Specialty or Google Professional Machine Learning Engineer preferred.