Job Description
Are you ready to architect the intelligence that defines the next decade? Nexus Horizon AI is seeking a visionary Senior Generative AI Engineer to lead the development of our proprietary LLM infrastructure. We are building the foundational technology for the year 2026 and beyond, and we need a technical mastermind to turn theoretical research into production-ready reality.
In this role, you will not just write code; you will shape the cognitive backbone of our ecosystem. You will be at the forefront of integrating state-of-the-art Agentic AI systems, optimizing inference pipelines, and ensuring our models are safe, scalable, and transformative.
Why You'll Thrive Here:
- Future-First Impact: Work on high-stakes projects that will set industry standards for the next generation of AI.
- Competitive Compensation: A top-tier salary package reflecting your expertise in the rapidly evolving AI landscape.
- Autonomy: The freedom to experiment with cutting-edge architectures (e.g., MoE, Sparse Transformers) and drive technical decisions.
If you possess an obsession for performance, a deep understanding of deep learning, and a passion for ethical AI, we invite you to join our elite engineering team.
Responsibilities
- Design and deploy scalable LLM architectures optimized for high-throughput, low-latency inference.
- Develop and maintain Retrieval-Augmented Generation (RAG) pipelines to ensure factual accuracy and context-aware responses.
- Implement advanced model fine-tuning and alignment techniques (e.g., RLHF, DPO) to enhance model behavior.
- Collaborate with cross-functional teams (Product, Data Science, Security) to integrate AI agents into seamless user experiences.
- Establish robust MLOps practices for model monitoring, versioning, and automated retraining pipelines.
- Contribute to the research and evaluation of novel AI architectures relevant to the 2026 roadmap.
Qualifications
- 5+ years of professional experience in software engineering, with a strong focus on Machine Learning or AI.
- Deep expertise in Python, PyTorch, and TensorFlow or JAX.
- Proven track record of working with Large Language Models (LLMs), Transformers, and generative models.
- Experience deploying models on cloud infrastructure (AWS, GCP, or Azure) using containerization (Docker/Kubernetes).
- Strong understanding of MLOps tools, data pipelines, and model evaluation frameworks.
- Excellent communication skills and the ability to translate complex technical concepts for diverse stakeholders.