Job Description
We are on the cusp of a technological revolution. At Nebula Future Systems, we are building the infrastructure for the 2026 era of Artificial Intelligence. We are seeking a visionary AI Architect to design and deploy autonomous cognitive agents that will redefine human-machine interaction.
In this role, you will not just adapt to future trends; you will help shape them. You will work at the intersection of advanced machine learning, neural architecture search, and scalable distributed systems. If you are passionate about solving the hardest problems in AI and have a passion for the future, we want to hear from you.
Why Join Us?
- Work on cutting-edge 2026 technology stack.
- Competitive compensation and equity packages.
- Flexible remote and hybrid work options.
- Access to top-tier research papers and compute resources.
Responsibilities
- Architect Neural Infrastructures: Design scalable, fault-tolerant neural network architectures optimized for the computational demands of 2026.
- Autonomous Agent Development: Lead the engineering of next-generation autonomous agents capable of complex, multi-step reasoning.
- Model Optimization: Implement techniques such as quantization, pruning, and distillation to deploy massive models efficiently on edge devices.
- R&D Leadership: Conduct research into emerging paradigms like Neuromorphic Computing and Quantum-Augmented AI.
- Collaboration: Partner with product teams to translate theoretical AI breakthroughs into practical, user-facing applications.
- Mentorship: Guide junior engineers and researchers, fostering a culture of innovation and technical excellence.
Qualifications
- Education: Master’s or PhD in Computer Science, Robotics, Mathematics, or a related field.
- Experience: 5+ years of professional experience in AI/ML engineering, with a focus on deep learning frameworks.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and distributed computing systems (Kubernetes, Docker).
- AI Specialization: Strong background in Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- Problem Solving: Demonstrated ability to solve complex, unstructured problems and optimize for performance and efficiency.
- Communication: Excellent written and verbal communication skills for technical documentation and stakeholder presentations.