Job Description
We are building the infrastructure for the future. NexaCore Technologies is looking for a visionary Principal AI Engineer to spearhead Project 2026, our ambitious initiative to redefine generative intelligence and quantum-enhanced machine learning.
In this role, you will architect the next generation of neural networks, ensuring our systems are not only powerful but also ethical, scalable, and ready for the demands of the year 2026 and beyond. You will work at the intersection of deep learning, reinforcement learning, and high-performance computing to solve complex, unsolved problems in natural language understanding and predictive analytics.
Why Join Us?
We offer a competitive equity package, a flexible remote-first culture, and the opportunity to work on technology that will shape the next decade.
Responsibilities
- Lead Architecture: Design and implement scalable, fault-tolerant AI models for Project 2026, focusing on efficiency and low-latency inference.
- Model Development: Push the boundaries of current generative AI models, exploring novel architectures like state-space models and hybrid quantum-classical systems.
- Research & Innovation: Stay at the forefront of AI research, translating academic breakthroughs into production-ready code and frameworks.
- Ethical AI: Establish and enforce rigorous safety guidelines and bias mitigation strategies for all deployed AI systems.
- Technical Leadership: Mentor a team of senior engineers and data scientists, fostering a culture of innovation and continuous learning.
- System Optimization: Optimize training pipelines and data infrastructure to handle petabyte-scale datasets efficiently.
- Stakeholder Communication: Collaborate with product leaders and C-suite executives to define the roadmap for AI-driven features.
Qualifications
- Education: PhD in Computer Science, Artificial Intelligence, Mathematics, or a related field (or equivalent extensive experience).
- Experience: 8+ years of professional experience in machine learning, deep learning, or AI research.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Experience with distributed training frameworks (Ray, Horovod) is highly preferred.
- Algorithmic Expertise: Strong understanding of transformer architectures, diffusion models, and reinforcement learning algorithms.
- Programming: Expert-level coding skills in at least one systems programming language (e.g., C++, Rust, or Go).
- Cloud & Infrastructure: Experience deploying large-scale AI workloads on AWS, GCP, or Azure using Kubernetes and Docker.
- Communication: Exceptional ability to communicate complex technical concepts to both technical and non-technical stakeholders.