Job Description
Join the Vanguard of AI Evolution
Nexus Horizon is a premier technology think-tank and product lab dedicated to defining the landscape of Artificial Intelligence in the year 2026 and beyond. We are not just building applications; we are architecting the future of human-machine symbiosis. We are seeking a visionary Lead AI Architect to lead our R&D division in developing next-generation Autonomous Agents and Cognitive Computing systems.
As the industry shifts towards agentic AI and synthetic data ecosystems, your role will be pivotal in designing scalable, ethical, and high-performance neural architectures. If you are passionate about pushing the boundaries of LLMs, Reinforcement Learning, and Edge AI, we want to hear from you.
Responsibilities
- Architect Next-Gen AI Systems: Design and deploy scalable, fault-tolerant AI architectures capable of handling millions of concurrent intelligent agents.
- Pioneer Research: Lead internal research initiatives into multimodal models, memory-augmented networks, and autonomous decision-making frameworks.
- Optimize Inference Pipelines: Engineer high-performance inference engines to reduce latency and optimize resource utilization for real-time applications.
- Model Governance: Establish and enforce strict ethical guidelines and safety protocols for Generative AI deployment to ensure bias mitigation and compliance.
- Cross-Functional Leadership: Mentor a team of senior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Strategic Roadmapping: Collaborate with product leaders to define the technical roadmap for our 2026 flagship products.
Qualifications
- Advanced Degree: Master’s or PhD in Computer Science, Machine Learning, or a related quantitative field from a top-tier institution.
- Technical Mastery: Deep expertise in Python, PyTorch, TensorFlow, and distributed computing frameworks (Kubernetes, Ray).
- Experience: 8+ years of experience in AI/ML engineering, with at least 3 years in a Lead or Architect role.
- Architecture: Proven track record of designing complex systems for large-scale Natural Language Processing (NLP) tasks.
- Tooling: Proficiency in MLOps tools (MLflow, Kubeflow) and cloud platforms (AWS, GCP, Azure).
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.