Job Description
Are you ready to architect the intelligence systems of tomorrow?
Nebula Innovations is seeking a visionary Senior AI Research Engineer to lead our cutting-edge R&D division. As we define the technological roadmap for 2026, we are looking for a pioneer who thrives on pushing the boundaries of what is possible in Artificial General Intelligence (AGI) and Quantum Neural Networks.
In this role, you won't just be maintaining legacy systems; you will be building the foundational architecture for a future where AI seamlessly integrates with human consciousness. You will work in a high-performance environment, collaborating with top-tier global talent to solve complex problems that have no immediate precedent.
Why join us?
- Work on projects that redefine the industry standards for 2026 and beyond.
- Competitive compensation package with equity options.
- Access to state-of-the-art computing infrastructure and quantum hardware.
If you are ready to lead the next generation of technological evolution, we want to hear from you.
Responsibilities
- Lead R&D: Spearhead the development of next-generation Neural Architecture Search (NAS) models designed for the 2026 compute landscape.
- Quantum Integration: Design hybrid quantum-classical algorithms to solve optimization problems currently considered unsolvable.
- Strategic Roadmap: Collaborate with the CTO to define the technical milestones and deliverables for the 2026 product cycle.
- Model Optimization: Engineer highly efficient, low-latency models capable of running on edge devices with limited power consumption.
- Mentorship: Cultivate a high-performance research team, conducting code reviews and technical workshops.
- Patents & Publications: Author technical papers and secure patents for novel AI methodologies.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Mathematics, Physics, or a related field with a focus on AI/ML.
- Experience: 5+ years of professional experience in Machine Learning, Deep Learning, or Reinforcement Learning.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and CUDA programming.
- Quantum Knowledge: Demonstrated experience or strong interest in quantum computing concepts (Qiskit, Cirq, or similar).
- Problem Solving: Proven ability to tackle ambiguous problems and deliver innovative solutions under tight deadlines.
- Communication: Excellent technical writing and public speaking skills for presenting research findings to stakeholders.