Research Scientist, Video

As a Research Scientist at Cantina, your key responsibilities include conducting research to develop advanced models and algorithms for image and video generation, publishing your findings in open-access formats to contribute to the AI community, and collaborating with product and design teams to implement prototypes. Additionally, you'll optimize models for efficiency, enhancing their applicability in real-world scenarios.

The Research Scientist position at Cantina requires a Ph.D. or equivalent experience in Computer Science, Electrical Engineering, or a related field with a focus on generative modeling, particularly in computer vision. Experience in areas such as image/video generation, audio modeling, and model optimization is beneficial, along with a proven track record of publications in top-tier conferences.

Yes, the Research Scientist position at Cantina is remote-friendly for candidates located in London or the GMT time zone. This flexibility allows you to work from the comfort of your home while contributing to cutting-edge AI technology.

The salary for the Research Scientist role at Cantina starts at $200,000 and can go up to $275,000, accompanied by a stock option plan and a competitive benefits package including healthcare and flexible work arrangements.

Candidates applying for the Research Scientist position at Cantina should possess strong programming skills in Python, along with experience using AI frameworks like PyTorch or TensorFlow. These skills will enable you to effectively develop and optimize generative models.

When answering this question, highlight specific projects where you applied generative modeling techniques. Discuss the methods used, challenges faced, and how your contributions advanced the project outcomes. Focus on your hands-on experience and any innovative solutions you developed.

Share your strategies for staying current, such as following leading AI journals, attending relevant conferences, participating in online communities, or engaging with ongoing research projects. Highlight how these activities inspire your work and contribute to your effectiveness as a Research Scientist.

To answer this question effectively, provide details about the project's initial challenges. Discuss your problem-solving approach, any adjustments you made to your methodology, and the results achieved. Emphasize collaboration and teamwork if applicable.

Explain how collaboration enhances your research quality. Share examples where input from product or design teams led to valuable insights or improvements in your models, showcasing your ability to work effectively within a multidisciplinary team.

Discuss the methodologies you find most effective, such as diffusion models, flow matching, or GANs. Justify your preferences by referencing specific projects or research findings, and illustrate how these methodologies can solve real-world challenges in content creation.

Mention the programming languages (like Python), libraries (such as PyTorch or TensorFlow), and any other tools you frequently utilize for your research. Share how these tools have facilitated your work and contributed to achieving successful outcomes in your projects.

Talk about your methodology for model optimization, including techniques you’ve employed and how you measure success. Emphasize the importance of balancing performance with computational efficiency and how this impacts real-world deployment.

Cite a specific publication, providing context about the research focus, methodology, and findings. Explain its impact on the field and how it has contributed to your credibility as a Research Scientist.

Discuss the criteria you use to assess model performance, such as accuracy, robustness, and generalizability. Provide examples where your testing process contributed to improved model outcomes or adaptations.

Articulate your enthusiasm for Cantina's mission and how your skills align with their goals. Focus on the innovative AI applications and the collaborative culture that attracts you to the organization.