Job Description
Join the Vanguard of Artificial Intelligence
Apex Neural Systems is at the forefront of defining the intelligence landscape of 2026. We are seeking a visionary Lead AI Architect to design and deploy the next generation of autonomous agents and reasoning models. In this role, you will architect systems that transcend simple text generation, moving towards autonomous decision-making and complex problem-solving.
You will be responsible for the end-to-end technical lifecycle of our AI infrastructure, ensuring our models are scalable, secure, and aligned with the rapid evolution of the AI ecosystem.
What You Will Do:
- Design scalable architectures for multi-agent systems and advanced LLM orchestration.
- Lead the research and implementation of cutting-edge Generative AI techniques.
- Optimize model inference for low-latency, high-volume environments.
- Establish AI governance frameworks to ensure ethical deployment and safety.
- Collaborate with cross-functional teams to translate futuristic research into production-ready products.
Qualifications:
- PhD or Master’s in Computer Science, AI, or a related technical field.
- 5+ years of experience in machine learning engineering and deep learning.
- Expert proficiency in Python, PyTorch, and TensorFlow.
- Proven experience with Large Language Models (LLMs), fine-tuning, and RAG architectures.
- Strong background in MLOps, cloud infrastructure (AWS/GCP), and containerization.
Responsibilities
- Design and implement scalable architectures for autonomous AI agents.
- Lead the integration of next-generation Large Language Models (LLMs) into production workflows.
- Optimize inference pipelines to ensure real-time performance and efficiency.
- Establish best practices for AI safety, fairness, and explainability.
- Collaborate with product and research teams to define the 2026 roadmap.
- Mentor junior engineers and foster a culture of technical innovation.
Qualifications
- PhD or Master’s in Computer Science, AI, or a related technical field.
- 5+ years of experience in machine learning engineering and deep learning.
- Expert proficiency in Python, PyTorch, and TensorFlow.
- Proven experience with LLMs, fine-tuning, and RAG architectures.
- Strong background in MLOps, cloud infrastructure, and containerization.
- Experience with reinforcement learning and multi-agent systems is highly preferred.