Job Description
Are you ready to architect the intelligence layer of the next generation of autonomous systems? At Nexus Horizon Labs, we are building the foundational infrastructure for the year 2026 and beyond.
We are looking for a visionary Senior AI Systems Architect to lead our core engineering team. You won't just be writing code; you will be defining the architectural paradigms that power next-gen decision-making engines and adaptive robotics.
In this role, you will bridge the gap between theoretical machine learning breakthroughs and production-grade reliability. You will oversee the deployment of Agentic AI workflows and ensure our systems are scalable, secure, and efficient at scale.
Responsibilities
- Architect and design high-performance, distributed AI systems capable of processing petabytes of real-time data.
- Lead the technical strategy for integrating Generative AI and Reinforcement Learning into core product infrastructure.
- Optimize model inference latency and reduce computational overhead for edge deployments.
- Establish best practices for MLOps, ensuring reproducibility and continuous integration/continuous deployment (CI/CD).
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate business needs into technical solutions.
- Conduct code reviews and mentor junior engineers to foster a culture of technical excellence.
- Stay ahead of industry trends in AI safety, alignment, and next-gen hardware acceleration (GPUs/TPUs).
Qualifications
- Ph.D. or Master’s degree in Computer Science, Machine Learning, or a related technical field.
- 10+ years of professional experience in software architecture, with at least 5 years specifically in AI/ML system design.
- Deep expertise in Python, C++, and distributed systems programming.
- Proven track record of deploying large-scale machine learning models to production environments.
- Strong understanding of neural network architectures, optimization techniques, and hardware acceleration.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Exceptional communication skills with the ability to articulate complex technical concepts to non-technical stakeholders.