Job Description
Are you ready to define the future of artificial intelligence? OmniFuture Systems is launching The 2026 Initiative, a bold project to engineer the next generation of sentient AI agents and autonomous systems. We are seeking a visionary AI Architect to lead our engineering division in building scalable, secure, and ethical generative models that will redefine human-machine interaction.
In this role, you will bridge the gap between theoretical AI research and practical, high-impact engineering. You will work at the cutting edge of Generative AI, integrating Large Language Models (LLMs) with emerging quantum-ready architectures. If you are passionate about solving complex problems and shaping the technological landscape of the future, we want to hear from you.
Why Join Us?
- Work on mission-critical projects that define the AI landscape of the next decade.
- Competitive equity package and performance bonuses.
- Top-tier benefits and a flexible, remote-first culture.
Responsibilities
- Architect and deploy state-of-the-art Large Language Models (LLMs) and Generative AI frameworks for enterprise applications.
- Lead the design of ethical AI frameworks, ensuring fairness, transparency, and bias mitigation in model outputs.
- Optimize model inference for low-latency, high-volume environments, utilizing edge computing and distributed systems.
- Collaborate with quantum computing researchers to prepare infrastructure for future-proofing our AI capabilities.
- Define technical roadmaps for the 2026 initiative, mentoring junior engineers and fostering a culture of innovation.
- Conduct rigorous code reviews and system architecture audits to ensure security and scalability.
Qualifications
- PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related quantitative field.
- 5+ years of professional experience in Deep Learning, Machine Learning, or Natural Language Processing (NLP).
- Expert proficiency in Python, PyTorch, and TensorFlow/Keras.
- Proven track record of deploying production-grade NLP models and LLMs (e.g., GPT, BERT, Llama).
- Strong understanding of Generative Adversarial Networks (GANs), Diffusion models, and Reinforcement Learning from Human Feedback (RLHF).
- Familiarity with cloud infrastructure (AWS, GCP, Azure) and containerization (Docker, Kubernetes).