Job Description
We are building the future of intelligence. Apex Horizon Technologies is seeking a visionary Senior Generative AI Architect to lead the development of next-generation Large Language Models (LLMs) and autonomous agents. If you are passionate about pushing the boundaries of what AI can achieve in 2026 and beyond, we want to hear from you.
In this role, you will define the architectural roadmap for our core AI systems, collaborate with world-class researchers, and deploy models that impact millions of users globally. You will be at the forefront of the Generative AI revolution, working in a fast-paced, innovative environment.
Why Join Us?
- Work on cutting-edge Generative AI and LLM technologies.
- Competitive compensation and equity package.
- Flexible remote-first culture with offices in SF.
- Opportunity to shape the roadmap for the next generation of AI products.
Responsibilities
- Architect LLM Pipelines: Design, implement, and optimize scalable end-to-end machine learning pipelines for training, fine-tuning, and deploying large language models.
- Research & Innovation: Stay ahead of the curve by researching novel transformer architectures and generative techniques to improve model performance and efficiency.
- Model Optimization: Lead efforts in model quantization, pruning, and serving to ensure low-latency, high-throughput inference in production environments.
- Technical Leadership: Mentor a team of ML engineers and data scientists, conducting code reviews and technical architecture discussions.
- Collaboration: Partner with product managers and engineers to translate business requirements into technical AI solutions.
- Ethical AI: Ensure AI systems are fair, transparent, and adhere to safety guidelines.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field (PhD preferred).
- Experience: 5+ years of professional experience in machine learning, deep learning, or natural language processing.
- Programming: Strong proficiency in Python, PyTorch, TensorFlow, or JAX.
- LLM Knowledge: Deep understanding of Transformer models, GPT architectures, and RAG (Retrieval-Augmented Generation) frameworks.
- MLOps: Experience with MLOps tools such as MLflow, Kubeflow, or AWS SageMaker.
- Problem Solving: Demonstrated ability to solve complex technical problems and improve model accuracy and robustness.