Job Description
Are you ready to define the future of Artificial Intelligence?
Nexus Horizon AI is on the cutting edge of the 2026 AI landscape, building next-generation generative models that reshape how humans interact with technology. We are seeking a visionary Senior AI/LLM Engineer to lead our technical strategy in Large Language Model optimization and deployment.
In this role, you won't just be maintaining models; you will be architecting the intelligence stack of tomorrow. You will work directly with our research team to push the boundaries of generative AI, ensuring our solutions are scalable, ethical, and revolutionary.
Why Join Us?
- Future-Forward Impact: Work on projects that will define the AI standards for the next decade.
- Top-Tier Compensation: Competitive salary and equity package reflecting market value in the 2026 tech ecosystem.
- Innovation Hub: Access to state-of-the-art infrastructure and the latest hardware for model training.
Responsibilities
- Architect & Deploy: Design and implement scalable LLM architectures, including RAG (Retrieval-Augmented Generation) pipelines and fine-tuning strategies for proprietary data.
- Model Optimization: Drive performance improvements in model inference speed and latency to support real-time applications.
- Research & Development: Experiment with emerging techniques in prompt engineering, model quantization, and multi-modal AI integration.
- System Reliability: Oversee MLOps pipelines to ensure continuous integration and delivery of AI models with high availability.
- Code Review & Mentorship: Lead technical reviews and mentor junior engineers and data scientists to foster a culture of excellence.
- AI Governance: Implement safety guardrails and bias mitigation strategies to ensure responsible AI deployment.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related technical field.
- Experience: 5+ years of professional experience in software engineering, specifically with Python, PyTorch, or TensorFlow.
- LLM Expertise: Proven track record of working with Large Language Models (e.g., GPT, Llama, Mistral) and fine-tuning methodologies.
- Infrastructure: Strong understanding of cloud platforms (AWS/GCP/Azure) and containerization technologies (Docker, Kubernetes).
- Problem Solving: Demonstrated ability to solve complex optimization problems and improve model efficiency.
- Communication: Excellent written and verbal communication skills for translating technical concepts to stakeholders.