Job Description
Are you ready to shape the artificial intelligence landscape of the future? Nexus Horizon Technologies is seeking a visionary Senior Generative AI Architect to join our elite '2026 Initiative.' We are building the next generation of autonomous, multimodal AI agents that will redefine enterprise efficiency. If you are passionate about pushing the boundaries of Large Language Models (LLMs), RAG architectures, and ethical AI deployment, this is your opportunity to lead.
In this high-impact role, you will design scalable infrastructure, mentor top-tier engineering talent, and ensure our models are safe, accurate, and future-proof.
Responsibilities
- Architect Future-Proof Models: Lead the design and implementation of cutting-edge Generative AI models, focusing on scalability and multimodal capabilities for the 2026 roadmap.
- Optimize Inference & Training: Engineer high-performance systems to reduce latency and cost, utilizing advanced techniques like model quantization and distillation.
- Ensure AI Safety & Alignment: Develop robust guardrails and RLHF (Reinforcement Learning from Human Feedback) pipelines to ensure model outputs align with safety and compliance standards.
- Build MLOps Pipelines: Construct end-to-end machine learning infrastructure using Kubernetes, Docker, and cloud-native services to streamline the deployment lifecycle.
- Drive Research & Innovation: Stay at the forefront of AI research, implementing state-of-the-art techniques from top-tier conferences (NeurIPS, ICML) into production systems.
- Cross-Functional Leadership: Collaborate closely with product managers, data scientists, and legal teams to translate complex technical requirements into real-world AI solutions.
Qualifications
- Education: Master’s degree or Ph.D. in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 5+ years of experience in Machine Learning and Deep Learning, with at least 2 years specifically focused on Generative AI or LLM development.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and Hugging Face Transformers; experience with LangChain and vector databases (Pinecone, Weaviate).
- Infrastructure: Strong experience with cloud platforms (AWS/GCP/Azure) and container orchestration (Docker, Kubernetes).
- Research Background: Proven ability to read and implement research papers; familiarity with modern architectures like Transformer variants and Diffusion models.
- Soft Skills: Excellent communication skills with the ability to translate technical jargon into business value for stakeholders.