Job Description
Join the Vanguard of Artificial Intelligence
Nexus Future Tech is redefining the trajectory of machine learning with a mission to engineer the intelligent systems of 2026. We are seeking a visionary Senior AI Architect to lead our flagship project, 'Project Horizon.' In this role, you will design and deploy the next generation of generative AI models that anticipate market needs and redefine human-computer interaction.
As a key member of our elite research division, you will bridge the gap between theoretical breakthroughs and scalable production systems. If you are passionate about the future of AI and possess the technical prowess to build systems that will operate at the forefront of the 2026 landscape, we want to hear from you.
Responsibilities
- Architect and implement state-of-the-art generative models (LLMs, Diffusion, Transformers) focused on the 2026 evolution of AI capabilities.
- Optimize model latency and throughput for real-time, high-volume inference environments.
- Lead research initiatives to improve model efficiency, reducing computational costs without sacrificing accuracy.
- Collaborate with cross-functional engineering teams to integrate AI agents into complex software ecosystems.
- Establish robust MLOps pipelines for model training, validation, and continuous deployment.
- Mentor junior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Define technical roadmaps for AI infrastructure that align with long-term business goals.
Qualifications
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- 8+ years of experience in machine learning, deep learning, or natural language processing.
- Expert proficiency in Python, PyTorch, and TensorFlow.
- Strong understanding of transformer architectures, attention mechanisms, and fine-tuning strategies.
- Proven experience deploying large-scale models in cloud environments (AWS, GCP, or Azure).
- Exceptional problem-solving skills and the ability to thrive in ambiguous, fast-paced environments.
- Experience with vector databases and RAG (Retrieval-Augmented Generation) architectures.