Job Description
Join NexusAI Solutions at the forefront of technological evolution as we pioneer breakthrough AI systems for 2026. We're seeking visionary AI/ML Engineers to architect next-generation autonomous frameworks that will redefine industries. Our Austin-based innovation hub combines cutting-edge research with agile development, offering unparalleled opportunities to shape the future of intelligent automation.
As a key member of our Future Tech Vision team, you'll collaborate with world-class researchers to develop scalable ML pipelines, implement quantum-resistant algorithms, and deploy solutions in real-world environments. We offer competitive equity packages, flexible work arrangements, and dedicated R&D time for personal projects.
Our culture embraces experimentation and values diverse perspectives. If you're passionate about solving complex challenges and pushing the boundaries of what's possible, we invite you to help build tomorrow's technology today.
Responsibilities
- Design and implement production-grade ML systems for autonomous decision-making platforms
- Develop quantum-resistant encryption models for secure AI communication protocols
- Create ethical AI governance frameworks aligned with 2026 regulatory standards
- Lead cross-functional teams in deploying edge-computing solutions for real-time inference
- Research and integrate emerging technologies (e.g., neuromorphic computing, swarm intelligence)
- Optimize neural architectures for energy-efficient deployment in IoT ecosystems
- Document technical specifications and conduct peer reviews for AI system components
Qualifications
- PhD or MS in Computer Science/AI with 5+ years of ML engineering experience
- Expertise in transformer architectures and federated learning methodologies
- Proficiency in PyTorch/TensorFlow and distributed computing frameworks
- Published research in top-tier AI conferences (NeurIPS, ICML, ICLR)
- Experience deploying ML models in production with Kubernetes and cloud-native stacks
- Strong background in ethical AI development and bias mitigation techniques
- Portfolio demonstrating complex ML system implementations from concept to deployment
- Certification in quantum computing fundamentals (preferred)