Job Description
Are you ready to architect the intelligence of tomorrow? Nexus Horizons is seeking a visionary Senior Generative AI Engineer to lead the development of next-generation Large Language Models (LLMs) and Agentic AI systems.
As we prepare for the technological landscape of 2026, we are building robust, scalable, and ethically aligned AI infrastructures. In this role, you will not just use existing tools; you will push the boundaries of what is possible in natural language processing and autonomous agents.
Why this role stands out:
- Future-Proof Technology: Work with cutting-edge LLMs (e.g., GPT-4, Claude, Llama 3) and emerging multimodal architectures.
- High Impact: Your code will power the core decision-making engines of our enterprise clients.
- Competitive Compensation: We offer a top-tier salary package and equity options for long-term growth.
Responsibilities
- Architect and deploy scalable generative AI models, including LLMs and diffusion models, for high-volume production environments.
- Lead the end-to-end machine learning lifecycle: data curation, training, fine-tuning, and rigorous evaluation.
- Optimize model inference latency and reduce operational costs using techniques like quantization, pruning, and distributed computing.
- Research novel architectures to enhance model reasoning capabilities and minimize hallucinations.
- Collaborate with product and engineering teams to integrate AI capabilities seamlessly into consumer and B2B products.
- Establish best practices for AI safety, fairness, and interpretability.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, Statistics, or a related technical field.
- 5+ years of professional experience in Machine Learning, Deep Learning, or Natural Language Processing.
- Expert proficiency in Python, PyTorch, TensorFlow, and modern MLOps tools (MLflow, Kubeflow, Ray).
- Proven experience fine-tuning open-source models on custom datasets using PEFT and LoRA techniques.
- Strong understanding of distributed systems, cloud infrastructure (AWS/GCP), and GPU cluster optimization.