Job Description
We are seeking a visionary Senior AI Infrastructure Engineer to join Nexus Horizon and architect the technological backbone for the year 2026. In this high-impact role, you will be at the forefront of deploying scalable, high-performance machine learning systems that redefine industry standards. You will not simply maintain existing infrastructure; you will build the foundation for the future of artificial intelligence.
As a key leader in our 2026 Vision initiative, you will bridge the gap between theoretical AI research and production-grade engineering. You will work with a world-class team to solve complex scalability challenges and implement next-generation MLOps strategies. If you are passionate about the convergence of quantum computing, generative AI, and distributed systems, we want to hear from you.
Responsibilities
- Architect and maintain scalable AI infrastructure pipelines capable of processing petabyte-scale data with low latency.
- Optimize deep learning frameworks and models for high-throughput inference on distributed GPU clusters.
- Implement advanced security and privacy-preserving technologies (e.g., Federated Learning, Homomorphic Encryption) to protect sensitive data.
- Lead the design and deployment of automated CI/CD pipelines for Machine Learning Operations (MLOps).
- Collaborate with researchers to translate novel algorithms into robust, production-ready software components.
- Ensure system reliability, fault tolerance, and operational excellence across all AI services.
Qualifications
- Master’s degree in Computer Science, Artificial Intelligence, or a related field (PhD preferred).
- 7+ years of experience in software engineering, with a strong focus on machine learning infrastructure.
- Deep proficiency in Python, C++, and ML frameworks such as PyTorch or TensorFlow.
- Extensive experience with cloud platforms (AWS, GCP, or Azure) and containerization (Kubernetes, Docker).
- Strong understanding of distributed systems, high availability architecture, and big data technologies (e.g., Spark, Kafka, Cassandra).
- Proven track record of leading technical projects and mentoring junior engineers in a fast-paced environment.