Job Description
Are you ready to define the AI landscape of 2026?
We are Nexus Horizon AI, a pioneering research lab in San Francisco, seeking a visionary Senior Generative AI Engineer to join our elite team. As we race towards the 2026 AI horizon, we are building the next generation of Multimodal Large Language Models (LLMs) that will redefine human-machine interaction.
In this role, you won't just be writing code; you will be architecting the intelligence layer for our enterprise clients. You will work at the intersection of cutting-edge research and scalable engineering, ensuring our models are safe, efficient, and ethically sound.
Why Join Us?
- Work on AGI-ready architectures designed for the 2026 roadmap.
- Competitive equity package with top-tier compensation.
- Flexible remote-first policy with a hub in the heart of SF.
Responsibilities
- Design, implement, and optimize Retrieval-Augmented Generation (RAG) pipelines to enhance model accuracy and reduce hallucinations.
- Conduct research and experimentation with state-of-the-art foundation models (e.g., LLaMA, Mistral, GPT-4 derivatives) to fine-tune for specific vertical use cases.
- Collaborate with data scientists and product managers to translate business requirements into technical AI solutions.
- Implement rigorous evaluation frameworks to measure model performance, safety, and bias.
- Ensure deployment scalability and low-latency inference for real-time applications.
- Stay ahead of the curve on emerging AI trends, particularly regarding multimodal capabilities expected by 2026.
Qualifications
- 5+ years of professional experience in software engineering, with at least 3 years specializing in Machine Learning or Deep Learning.
- Strong proficiency in Python, PyTorch, or TensorFlow.
- Deep understanding of NLP concepts, including tokenization, attention mechanisms, and transformer architectures.
- Experience with model fine-tuning, LoRA, and Quantization techniques.
- Experience deploying models via API (FastAPI, Flask) or cloud platforms (AWS, GCP, Azure).
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field.
- A passion for the ethical implications of AI and a commitment to building responsible technology.