Job Description
Join Nexus Horizon Systems as we architect the foundational technologies for the 2026 era. We are seeking a visionary Lead AI Architect to spearhead our next-generation machine learning infrastructure. In this pivotal role, you will define the technical roadmap for our AI strategy, ensuring scalability, security, and ethical implementation of future-ready algorithms. You will work closely with cross-functional teams to transform complex data into intelligent systems that redefine industry standards.
Our ideal candidate is not just familiar with current tech stacks but is already anticipating the paradigms of 2026, including advanced Generative AI, Neuro-symbolic computing, and Edge AI optimization.
Our ideal candidate is not just familiar with current tech stacks but is already anticipating the paradigms of 2026, including advanced Generative AI, Neuro-symbolic computing, and Edge AI optimization.
Responsibilities
- Design and architect scalable, high-performance machine learning pipelines and neural network architectures tailored for 2026 market demands.
- Lead the technical vision for the company's AI strategy, mentoring a team of senior data scientists and ML engineers.
- Oversee the deployment of Large Language Models (LLMs) and ensure robust fine-tuning strategies for specific verticals.
- Establish best practices for data governance, model explainability, and AI ethics compliance.
- Collaborate with product management to translate business requirements into technical AI roadmaps.
- Optimize existing infrastructure for reduced latency and increased throughput in distributed environments.
- Stay ahead of emerging trends in quantum computing integration and AI hardware acceleration.
Qualifications
- 10+ years of experience in software engineering, with at least 5 years specifically in AI/ML architecture and leadership.
- Deep expertise in Python, PyTorch, TensorFlow, and modern MLOps tooling.
- Proven track record of deploying production-grade AI systems handling petabytes of data.
- Strong understanding of distributed systems, cloud architecture (AWS/Azure/GCP), and containerization (Kubernetes/Docker).
- Experience with edge computing frameworks and real-time inference optimization.
- Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Exceptional communication skills with the ability to articulate complex technical concepts to non-technical stakeholders.