Job Description
Join Nexus Labs at the forefront of 2026's technological revolution. We're pioneering quantum computing applications and next-generation AI systems that will redefine human-machine interaction. As an AI Research Scientist, you'll collaborate with Nobel laureates and industry disruptors in our Austin innovation hub, where your work directly impacts global infrastructure, healthcare diagnostics, and sustainable energy solutions.
Our lab operates at the intersection of theoretical physics and applied machine learning, offering unprecedented resources for groundbreaking research. You'll lead projects in neuromorphic computing, ethical AI frameworks, and autonomous system optimization while mentoring the next generation of researchers.
Responsibilities
- Design and implement novel neural architectures for quantum-enhanced machine learning models
- Lead cross-functional teams in developing ethical AI governance frameworks for 2026 regulatory landscapes
- Author peer-reviewed publications and patents in top-tier AI/quantum computing journals
- Optimize computational models for real-time deployment in autonomous systems
- Collaborate with quantum hardware teams to develop hybrid AI-quantum algorithms
- Establish research protocols for large-scale AI safety and alignment testing
- Secure $5M+ in government and industry research grants annually
Qualifications
- PhD in Computer Science, Quantum Physics, or related field with 5+ years industry experience
- Published research in Nature/Science journals on quantum machine learning or neuromorphic systems
- Expertise in TensorFlow Quantum, Cirq, or equivalent quantum ML frameworks
- Proven track record of developing production-scale AI systems with >99.9% accuracy
- Deep understanding of transformer architectures and attention mechanisms
- Familiarity with NISQ-era quantum hardware limitations and error mitigation strategies
- Strong background in differential privacy and federated learning techniques
- Experience securing DARPA/EU Horizon Europe research funding