Job Description
Shape the Future of Intelligence. OmniLogic Solutions is pioneering the next generation of autonomous AI systems. We are seeking a visionary Senior AI Architect (2026 Vision) to lead our R&D efforts in building scalable, multimodal, and agentic AI frameworks.
In this role, you will not just write code; you will define the architectural paradigms that will power enterprise solutions for the next decade. You will bridge the gap between theoretical machine learning breakthroughs and production-grade software engineering.
Why Join Us?
- Work with state-of-the-art LLMs and transformer architectures.
- Competitive compensation package with equity opportunities.
- Flexible remote-first culture with a San Francisco hub.
- Focus on high-impact, long-term AI research.
Responsibilities
- Architect and implement next-generation AI pipelines capable of handling real-time multimodal data streams.
- Lead the research and integration of cutting-edge LLM techniques, including RAG (Retrieval-Augmented Generation) and fine-tuning strategies.
- Design scalable MLOps infrastructure to ensure model deployment, monitoring, and continuous improvement.
- Collaborate with cross-functional teams (product, engineering, design) to translate complex AI capabilities into user-friendly applications.
- Mentor junior data scientists and engineers, fostering a culture of innovation and technical excellence.
- Conduct rigorous performance optimization and security audits on AI models.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related technical field (or equivalent professional experience).
- 5+ years of experience in machine learning, deep learning, or AI research.
- Expert proficiency in Python, PyTorch, or TensorFlow.
- Strong understanding of large language models (LLMs), natural language processing (NLP), and generative AI models.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Proven track record of deploying production-ready AI systems at scale.