Job Description
We are pioneering the next generation of artificial intelligence with our flagship initiative, Project 2026. As a Senior AI Engineer, you will be at the forefront of building scalable, ethical, and transformative machine learning systems. Our mission is to redefine human-machine interaction by 2026, and we need a technical visionary to lead our architecture and development efforts.
In this role, you will work in a dynamic, high-performance environment focused on cutting-edge research and real-world application. You will collaborate with a world-class team of data scientists, engineers, and product strategists to deliver solutions that are not only technically superior but also socially responsible.
Join us in shaping the future of technology and be part of a company that is committed to excellence, innovation, and the advancement of human potential.
Responsibilities
- Architect and implement state-of-the-art deep learning models for predictive analytics and automation.
- Lead the full machine learning lifecycle, from data ingestion and cleaning to model training and deployment.
- Collaborate with cross-functional teams to define product requirements and technical roadmaps for the 2026 initiative.
- Optimize existing neural networks for high-speed inference on edge devices and cloud infrastructure.
- Mentor junior engineers and foster a culture of technical excellence, continuous learning, and innovation.
- Ensure data privacy, security compliance, and ethical AI practices throughout the development process.
Qualifications
- Master’s or Ph.D. in Computer Science, Mathematics, Statistics, or a related quantitative field.
- 5+ years of professional experience in AI/ML engineering, with a focus on Python and deep learning frameworks.
- Proven experience deploying scalable ML models in production environments using cloud services (AWS, GCP, or Azure).
- Strong expertise in Natural Language Processing (NLP) or Computer Vision is highly desirable.
- Familiarity with MLOps tools and practices (Kubernetes, Docker, MLflow, Airflow).
- Excellent problem-solving skills and the ability to thrive in a fast-paced, agile startup culture.