About the Role:
We are seeking exceptional AI Research Scientists with a deep passion for advancing the state of artificial intelligence and machine learning. This role focuses on fundamental and applied research in deep learning, large-scale models, and related areas—not on product engineering or system integration. Researchers will work on original ideas, publish results, and collaborate with leading experts to push boundaries in AI.
Responsibilities:
- Conduct original research in deep learning, generative models, reinforcement learning, or related areas.
- Develop, analyze, and publish new methods, algorithms, or architectures.
- Collaborate with cross-functional teams of researchers to explore emerging directions in AI theory and practice.
- Present findings at top conferences (NeurIPS, ICLR, ICML, CVPR, etc.).
- Prototype and validate novel approaches through empirical studies and experiments.
- Stay at the forefront of the AI research landscape and contribute to the organization’s long-term research vision.
Qualifications:
- 0-7 years of experience
- PhD in Computer Science, Machine Learning, Deep Learning, or a related field.
- Strong record of research excellence demonstrated through publications in top AI venues.
- Deep knowledge of modern deep learning architectures (e.g., transformers, diffusion models, large language models).
- Strong theoretical background in optimization, probabilistic modeling, or representation learning.
- Proficiency with at least one deep learning framework (e.g., PyTorch, JAX, TensorFlow).
- Ability to work collaboratively and contribute meaningfully to academic and applied research projects.
Preferred Experience:
- Prior experience in AI research labs or advanced industrial research teams.
- Contributions to open-source ML projects or papers demonstrating innovative thinking.
- Interest in exploring connections between AI theory and real-world applications such as language, vision, or reasoning.
Why Join Us:
- Collaborate with world-class researchers tackling frontier challenges in AI.
- Freedom to pursue long-term, high-impact research directions.
- Publish and present work openly within the global AI community.
- Remote-first culture supporting flexibility and deep focus.
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