Job Description
Are you ready to build the intelligence of tomorrow?
Apex Horizon Tech is at the forefront of the AI revolution, defining the tech stack of 2026. We are seeking a visionary Lead Generative AI Engineer to spearhead the development of next-generation Large Language Models (LLMs) and autonomous agents. If you are passionate about pushing the boundaries of what is possible with Generative AI and want to lead a world-class team, we want to meet you.
In this pivotal role, you will not just write code; you will architect the future of human-computer interaction, creating systems that are safe, scalable, and indistinguishable from human creativity.
Responsibilities
- Architect Next-Gen Models: Design and implement cutting-edge generative AI architectures, focusing on LLMs, diffusion models, and multimodal systems for the 2026 landscape.
- Model Optimization: Lead efforts in model compression, quantization, and inference optimization to deploy powerful AI on edge devices and massive cloud infrastructures.
- R&D Leadership: Conduct high-level research to explore emerging AI paradigms, including Chain-of-Thought reasoning and agentic workflows.
- Team Mentorship: Mentor junior engineers and data scientists, fostering a culture of innovation, technical excellence, and continuous learning.
- Production Deployment: Oversee the full lifecycle of AI models—from research prototyping to production-grade deployment using robust MLOps pipelines.
- Ethical AI Advocacy: Ensure all developed models adhere to strict safety guidelines, bias mitigation standards, and ethical AI frameworks.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Mathematics, Physics, or a related field with a focus on Machine Learning or Artificial Intelligence.
- Technical Expertise: Deep proficiency in Python, PyTorch, or TensorFlow, with extensive experience in Deep Learning frameworks.
- Generative AI Experience: Proven track record of working with Large Language Models (GPT-4, Llama, etc.), fine-tuning techniques (LoRA, P-Tuning), and RAG (Retrieval-Augmented Generation) architectures.
- System Design: Strong understanding of distributed systems, high-performance computing, and cloud infrastructure (AWS, GCP, or Azure).
- Problem Solving: Ability to tackle complex, open-ended problems in natural language processing and reasoning.
- Leadership: Demonstrated experience leading engineering teams and managing cross-functional projects from concept to launch.