Job Description
We are at the forefront of the technological revolution, and we are looking for a visionary AI Systems Architect to help us build the intelligent infrastructure of tomorrow. As part of our 2026 strategic roadmap, you will design and deploy scalable machine learning systems that redefine human-machine interaction.
In this role, you will bridge the gap between cutting-edge AI research and robust, production-grade engineering. You will lead a high-performing team, architecting solutions that are not only powerful but also ethical and sustainable. If you are passionate about the future of AI and want to leave a lasting impact, this is your opportunity to lead the charge.
Why Join Us?
- Work on next-generation generative AI models.
- Competitive compensation and equity packages.
- Flexible remote and hybrid work options.
- Access to state-of-the-art computing resources.
Responsibilities
- Architectural Leadership: Design and oversee the implementation of scalable, distributed AI infrastructure and cloud-native solutions.
- Model Deployment: Lead the end-to-end deployment of large-scale machine learning models, ensuring high availability and low latency.
- Roadmap Strategy: Define the technical vision and roadmap for our AI products through 2026 and beyond.
- Performance Optimization: Continuously optimize model inference pipelines and hardware utilization for maximum efficiency.
- Team Mentorship: Mentor junior engineers and data scientists, fostering a culture of technical excellence and innovation.
- Compliance & Ethics: Establish frameworks for ethical AI usage, data privacy, and algorithmic transparency.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 8+ years of experience in software engineering, with at least 4 years specifically focused on AI/ML system architecture.
- Technical Skills: Expert proficiency in Python, TensorFlow, PyTorch, and Kubernetes. Strong experience with cloud platforms (AWS, GCP, or Azure).
- AI Expertise: Deep understanding of Large Language Models (LLMs), transformers, and generative AI architectures.
- Problem Solving: Proven ability to solve complex technical challenges in high-stakes environments.
- Leadership: Demonstrated experience leading cross-functional teams and driving technical projects from conception to delivery.