Job Description
Are you ready to engineer the future of intelligence? Nexus Horizon Labs is seeking a visionary Senior Generative AI Engineer to lead our roadmap for 2026 and beyond. We are building the next generation of adaptive AI systems that redefine human-machine interaction. If you thrive in a high-performance environment and want to push the boundaries of Large Language Models (LLMs) and multimodal architectures, this is your opportunity.
In this role, you will not just use existing tools; you will help shape the architecture of the AI landscape. You will work with cutting-edge hardware and collaborate with world-class researchers to deploy models that scale efficiently.
Why join Nexus Horizon Labs?
- Future-Proof Technology: Work on core technologies planned for our 2026 global rollout.
- Top-Tier Compensation: Competitive salary plus equity in a high-growth startup.
- Flexible Environment: Hybrid work model supporting your best creative output.
Responsibilities
- Design, train, and fine-tune state-of-the-art Large Language Models (LLMs) and diffusion models.
- Optimize model inference performance on GPU clusters to ensure low-latency, high-throughput deployments.
- Collaborate with product teams to translate complex AI capabilities into intuitive user interfaces.
- Implement robust data pipelines for training and continuous learning systems.
- Conduct rigorous testing and evaluation of model safety, bias, and accuracy.
- Stay ahead of the curve by researching emerging architectures like Mixture-of-Experts and RAG.
Qualifications
- PhD or Master's degree in Computer Science, Mathematics, or a related technical field.
- 5+ years of professional experience in Machine Learning, Deep Learning, or AI research.
- Expert proficiency in Python and deep learning frameworks (PyTorch or TensorFlow).
- Strong understanding of distributed systems and cloud infrastructure (AWS, GCP, or Azure).
- Experience with model quantization, pruning, and optimization techniques.
- Demonstrated ability to publish in top-tier conferences (NeurIPS, ICML, ICLR) is a major plus.