Job Description
We are on a mission to engineer the technological reality of the year 2026. OmniFuture Systems is seeking a visionary Senior AI Research Scientist to lead our cutting-edge initiatives in Generative AI, Quantum Machine Learning, and Human-Computer Interaction. If you are passionate about pushing the boundaries of what is possible and defining the roadmap for the next decade of innovation, we want to meet you.
In this role, you won't just be maintaining current systems; you will be architecting the foundational intelligence that powers our ecosystem. You will work in a high-performance environment with access to state-of-the-art compute resources and a team of world-class engineers and ethicists. We offer a competitive compensation package, equity opportunities, and the freedom to explore high-risk, high-reward research areas.
Why Join Us?
- Work on projects that directly impact the future of global communication and automation.
- Collaborate with thought leaders in AI, Robotics, and Data Science.
- Flexible remote-first culture with quarterly innovation sprints in our SF hub.
Responsibilities
- Lead the R&D strategy for proprietary Large Language Models (LLMs) and multimodal systems targeted for deployment by 2026.
- Design and implement novel algorithms that improve model efficiency, accuracy, and scalability in edge computing environments.
- Bridge the gap between theoretical research and practical engineering, ensuring research outcomes are production-ready.
- Conduct rigorous A/B testing and validation of AI models to ensure safety, fairness, and alignment with human values.
- Publish high-impact research papers and present findings at top-tier international conferences (NeurIPS, ICML, ICLR).
- Mentor junior researchers and data scientists, fostering a culture of continuous learning and technical excellence.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Artificial Intelligence, Mathematics, or a related quantitative field.
- Minimum of 5+ years of experience in applied machine learning research or a comparable senior engineering role.
- Deep expertise in PyTorch, TensorFlow, or JAX, with a strong portfolio of open-source contributions.
- Proven track record of publishing in top-tier AI conferences or delivering significant results in large-scale production environments.
- Strong understanding of Deep Learning architectures, specifically Transformers, GANs, and Diffusion models.
- Experience with MLOps pipelines, model serving, and cloud infrastructure (AWS, GCP, or Azure).