Job Description
Join Nexus Innovations at the forefront of 2026's technological revolution. We're pioneering AI-driven solutions that will redefine industries by 2026, and we need visionary research scientists to lead this transformation. Our state-of-the-art labs in San Francisco offer unparalleled resources to develop breakthrough algorithms in machine learning, quantum computing, and neural networks. You'll collaborate with Nobel laureates and industry disruptors to solve humanity's most complex challenges while shaping the next decade of innovation.
Why Nexus?
- Unlimited R&D budget with cutting-edge infrastructure
- Equity grants and 401(k) matching for long-term growth
- Patent ownership on all innovations
- Flexible remote-first culture with quarterly in-person summits
Responsibilities
- Lead advanced research in generative AI and neural network optimization
- Develop scalable ML models for 2026-era autonomous systems
- Collaborate with quantum computing teams to hybridize classical-quantum algorithms
- Author peer-reviewed publications and present at premier conferences
- Mentor junior researchers and cross-functional engineering teams
- Secure 3+ patents annually in applied AI domains
- Translate theoretical breakthroughs into production-ready solutions
Qualifications
- PhD in Computer Science, AI, or related field (or equivalent experience)
- 5+ years of applied research in deep learning or reinforcement learning
- Published work in NeurIPS, ICML, or Nature Machine Intelligence
- Expertise in PyTorch/TensorFlow with distributed training frameworks
- Proven track record of deploying research to production systems
- Strong background in computational complexity theory
- Experience with quantum computing APIs (Qiskit, Cirq)
- Portfolio of open-source projects with 1k+ GitHub stars