Job Description
Join Nexus Dynamics at the forefront of AI innovation as we redefine technological boundaries for 2026. We seek a visionary AI/ML Systems Architect to design and deploy next-generation neural networks that power autonomous systems, predictive analytics, and human-AI collaboration ecosystems. This role offers unparalleled opportunity to shape the future of intelligent automation while working with Fortune 500 clients in healthcare, finance, and climate tech.
Our cutting-edge R&D lab combines quantum computing prototypes with neuromorphic hardware to achieve breakthroughs in unsupervised learning and ethical AI. You'll lead cross-functional teams of researchers, engineers, and domain experts to transform theoretical models into production-grade solutions with real-world impact.
Responsibilities
- Architect scalable ML pipelines using TensorFlow/PyTorch and distributed computing frameworks
- Design ethical AI governance frameworks ensuring compliance with EU AI Act and IEEE 7000 standards
- Lead deployment of multimodal AI systems processing text, vision, and sensor data
- Optimize model inference for edge devices and quantum hybrid computing environments
- Develop continuous learning systems enabling autonomous model adaptation
- Collaborate with product teams to translate business requirements into technical specifications
- Research emerging AI paradigms including neuro-symbolic AI and generative adversarial networks
Qualifications
- PhD or MS in Computer Science/AI with 5+ years of ML systems architecture experience
- Expertise in MLOps tools (Kubeflow, MLflow) and cloud-native deployment (AWS/GCP)
- Published research in top-tier AI conferences (NeurIPS, ICML) or equivalent industry impact
- Proficiency in low-latency model optimization and hardware acceleration (CUDA, TensorRT)
- Deep understanding of AI ethics, bias mitigation, and explainable AI techniques
- Experience with federated learning and privacy-preserving ML frameworks
- Track record of leading AI projects from prototype to production at scale