Job Description
We are building the infrastructure for the year 2026. As a Senior AI Architect at Nexus Future Systems, you won't just be writing code; you will define the trajectory of Artificial General Intelligence (AGI) and next-generation generative models. We are seeking a visionary engineer to lead our research division, bridging the gap between theoretical AI breakthroughs and scalable production systems.
In this role, you will work at the forefront of technology, tackling complex challenges in large language models, autonomous agents, and predictive analytics. If you are passionate about shaping the future and want to leave a lasting impact on the industry, we want to hear from you.
Responsibilities
- Architect Scalable AI Systems: Design and implement robust, scalable, and secure machine learning infrastructure capable of supporting enterprise-grade applications.
- Lead Research Initiatives: Spearhead research into cutting-edge algorithms, focusing on efficiency, accuracy, and ethical AI deployment.
- Model Optimization: Fine-tune and optimize large language models (LLMs) to ensure high performance and low latency in real-world environments.
- Technical Mentorship: Guide a team of talented engineers and data scientists, fostering a culture of innovation and continuous learning.
- Cross-Functional Collaboration: Partner with product managers and stakeholders to translate complex technical requirements into actionable roadmaps.
- Risk Management: Identify potential biases and technical risks in AI models to ensure responsible and compliant AI development.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- Experience: Minimum of 5+ years of professional experience in AI/ML engineering, with at least 2 years in a leadership or architect role.
- Technical Skills: Deep proficiency in Python, TensorFlow, PyTorch, and Hugging Face.
- Modeling: Extensive experience with Large Language Models (GPT, BERT, Llama) and generative AI frameworks.
- Cloud Expertise: Strong background in cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Problem Solving: Exceptional ability to solve complex technical problems and design systems that are both innovative and maintainable.