Job Description
We are currently seeking a visionary Senior AI Architect to lead our 2026 Horizon Initiative. As we stand on the brink of a new era in artificial intelligence, you will be tasked with architecting the core infrastructure that powers our next generation of autonomous systems. This is a rare opportunity to shape the technological landscape of the future.
Our Mission
To democratize advanced intelligence by building scalable, ethical, and efficient AI models that solve complex real-world problems. We are looking for a leader who can bridge the gap between theoretical research and production-grade deployment.
What You'll Do
- Design and implement scalable neural network architectures tailored for the 2026 roadmap.
- Lead the research and development of novel algorithms in Natural Language Processing (NLP) and Computer Vision.
- Oversee the end-to-end MLOps pipeline, ensuring model reliability, security, and performance.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to define technical requirements.
- Drive technical decision-making regarding hardware acceleration and cloud infrastructure optimization.
- Mentor junior engineers and establish a culture of innovation and technical excellence.
Responsibilities
- Architect and deploy large-scale machine learning models with a focus on latency and throughput.
- Conduct cutting-edge research to stay ahead of industry trends in generative AI and multimodal learning.
- Establish best practices for data governance, model versioning, and continuous integration/continuous deployment (CI/CD).
- Identify and mitigate risks associated with AI model bias and security vulnerabilities.
- Present technical roadmaps and architectural designs to executive leadership and stakeholders.
Qualifications
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- 8+ years of professional experience in machine learning engineering or applied AI research.
- Deep proficiency in Python, PyTorch, TensorFlow, or JAX.
- Extensive experience with distributed systems and cloud platforms (AWS, GCP, or Azure).
- Strong background in deep learning frameworks, including Transformers and RNNs.
- Proven track record of leading technical teams and managing complex projects.