Job Description
We are seeking a visionary Senior AI Architect to lead the architectural vision for Project 2026, our groundbreaking initiative in next-generation artificial intelligence infrastructure. At Nexus AI Labs, we are building the neural foundations for the future, and you will be at the forefront of this revolution.
In this role, you will define the technical strategy for large-scale machine learning systems, ensuring scalability, security, and performance. You will collaborate with world-class researchers and engineers to deploy state-of-the-art models that redefine human-machine interaction. If you are passionate about shaping the technological landscape of 2026 and beyond, we want to hear from you.
About You
You are not just a coder; you are a technical architect with a deep understanding of deep learning, distributed systems, and cloud-native technologies. You thrive in ambiguous environments and have a proven track record of delivering complex AI solutions.
Responsibilities
- Architectural Design: Design and implement robust, scalable, and secure AI infrastructure for Project 2026, leveraging cloud-native technologies and edge computing solutions.
- Model Optimization: Lead the optimization of large language models and neural networks for production deployment, focusing on inference speed and cost-efficiency.
- Team Leadership: Mentor a team of junior and mid-level data scientists and engineers, fostering a culture of innovation and technical excellence.
- Technical Strategy: Define the long-term technical roadmap for AI research and development, evaluating emerging technologies like quantum computing and neuromorphic chips.
- Collaboration: Partner with product managers and stakeholders to translate business requirements into technical specifications.
- Risk Management: Identify potential technical risks and implement mitigation strategies to ensure project delivery timelines.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 5+ years of experience in software engineering, with at least 3 years focused on AI/ML architecture.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and experience with MLOps pipelines (Kubeflow, MLflow).
- Cloud Expertise: Deep experience with AWS, Azure, or GCP in designing high-availability systems.
- Problem Solving: Strong analytical skills with a demonstrated ability to solve complex engineering challenges.
- Communication: Excellent verbal and written communication skills, capable of presenting technical concepts to non-technical audiences.